Apparatus and method to improve precision of identifying a range of effects of a failure in a system providing a multilayer structure of services

ABSTRACT

An apparatus obtains, from a first device, an identifier of a higher-order service for which occurrence of an abnormality or a possibility of being affected by an abnormality has been detected, where the first device searches for a range of effects of failure within a higher-order service layer that provides a higher-order service using a service provided in an object-service layer within a cloud service providing a layered structure of services. The apparatus determines a service within the object-service layer, which is reachable by tracing relations among services from the detected higher-order service, to be an in-effect-range service for which there is a possibility of being affected by an abnormality, and transmits the identifier of the in-effect-range service to a second device that searches for a range of effects of failure at a lower-order service layer that provides a lower-order service used to provide a service within the object-service layer.

CROSS-REFERENCE TO RELATED APPLICATION

This application is based upon and claims the benefit of priority of theprior Japanese Patent Application No. 2017-254294, filed on Dec. 28,2017, the entire contents of which are incorporated herein by reference.

FIELD

The embodiments discussed herein are related to apparatus and method toimprove precision of identifying a range of effects of a failure in asystem providing a multilayer structure of services.

BACKGROUND

In a case where a failure occurs in a part of equipment in a computernetwork system, equipment dependent on that equipment is also affectedby the failure. Equipment affected by a failure may exhibit operatingspeed slower than normal, inability to execute application programs, andso forth, for example. The effects of such a failure, which are alsoreferred to as failure impact, occur as a chain reaction through thenetwork. In a large-scale system, for example, many such equipment arein a dependency relation. Accordingly, the effects of a failure is notrestricted to the equipment where the trouble is occurring and equipmentdirectly connected to that equipment, but to various types of equipmentin the periphery thereof.

In a case where a failure occurs at certain equipment and otherequipment is affected by that failure, there may be cases where a usernotices the effects of the failure, but there may be cases where theuser does not notice even though affected by the failure, depending onthe equipment. In a case where the user does not notice being affectedby the failure, the system administrator is not notified by the userthat there is equipment affected by the failure, and the administratordoes not take measures. There also is equipment that currently is notaffected due to no load thereupon (no application program or the likebeing executed) at the time of the failure occurring, but likely will beaffected under load.

Equipment regarding which the user has not noticed the effects of thefailure, or currently is not affected due to no load, may be the causeof trouble hereafter. Accordingly, it is important for the systemadministrator to recognize such a group of equipment that may beaffected (range of effects, or range of influences), in order to operatethe system in a stable manner.

Examples of technology for identifying the state of the range of effectsof a failure include technology for visualizing range of effects offailures and so forth in an object system taking into consideration acloud environment, failure tolerability, and so forth. There also is anadministration management device that enables display with range ofeffects regarding individual failures and cause portions regardingindividual service failures sectioned off. Further, there also istechnology where the relation of calculator resources that a virtualserver uses is comprehensively expressed by a tree structure, andstatistical information of virtual resources that share physicalresources are automatically compiled.

The above related art is described in, for example, Japanese Laid-openPatent Publication Nos. 2012-38028, 2015-22396, and 2012-99048.

SUMMARY

According to an aspect of the embodiments, an apparatus obtains, from ahigher-order effect range identifying device configured to search for arange of effects of failure within a higher-order service layer thatprovides a higher-order service using a service provided in an objectservice layer within a cloud service where services being provided havea layered structure, an identifier of a detected higher-order serviceregarding which occurrence of an abnormality or a possibility of beingaffected by an abnormality has been detected. The apparatus determines,based on search route information indicating a search route to searchfor a service within a range of effects of failure from a start pointservice, a service within the object service layer that is reachable bytracing relations among services from the detected higher-order serviceby following a search route in a case where the detected higher-orderservice is the start point service, to be a first in-effect-rangeservice regarding which there is a possibility of being affected by anabnormality, and transmits the identifier of the first in-effect-rangeservice to a lower-order effect range identifying device configured tosearch for a range of effects of failure at a lower-order service layer,which is a source of providing a lower-order service that is used toprovide a service within the object service layer.

The object and advantages of the invention will be realized and attainedby means of the elements and combinations particularly pointed out inthe claims.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory and arenot restrictive of the invention.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram illustrating an example of a system according to afirst embodiment;

FIG. 2 is a diagram illustrating a system configuration example of asecond embodiment;

FIG. 3 is a diagram illustrating a configuration example of hardware ofa server;

FIG. 4 is a diagram illustrating an example of a cloud service;

FIG. 5 is a diagram illustrating transmission paths of information amongeffect range identifying devices;

FIG. 6 is a block diagram illustrating an example of functions of aneffect range identifying device;

FIG. 7 is a diagram illustrating an example of an effect range searchroute information storage unit;

FIG. 8 is a diagram illustrating an example of a search route;

FIG. 9 is a diagram illustrating an example of a stack operation model;

FIG. 10 is a diagram illustrating an example of functions of a stackinformation management unit;

FIG. 11 is a flowchart illustrating an example of procedures for ownstack No. registration processing;

FIG. 12 is a diagram illustrating an example of own stack No.registration processing results;

FIG. 13 is a flowchart illustrating an example of procedures for otherstack No. registration processing;

FIG. 14 is a diagram illustrating an example of other stack No.registration processing results;

FIG. 15 is a diagram illustrating an example of functions of a downflowprocessing unit;

FIG. 16 is a diagram illustrating an example of procedures of downflowprocessing;

FIG. 17 is a diagram illustrating detection examples of failure-detectedequipment and failure-affected equipment;

FIG. 18 is a diagram illustrating an example of detection informationobtaining processing;

FIG. 19 is a flowchart illustrating an example of procedures ofdetection information obtaining processing;

FIG. 20 is a diagram illustrating an example of information collectionprocessing;

FIG. 21 is a flowchart illustrating an example of information collectionprocessing;

FIG. 22 is a diagram illustrating an example of effect range searchingprocessing in downflow processing;

FIG. 23 is a diagram illustrating an example of stack operation modelreflecting detection information;

FIG. 24 is a diagram illustrating an example of a stack operation modelreflecting search results of a range of effects in downflow processing;

FIG. 25 is a flowchart illustrating procedures for effect rangesearching processing in downflow processing;

FIG. 26 is a diagram illustrating an example of search resultsnotification processing in downflow processing;

FIG. 27 is a flowchart illustrating an example of procedures of searchresults notification processing as to a lower-order stack;

FIG. 28 is a diagram illustrating an example of a range of effects offailure at a lowest-order stack;

FIG. 29 is a diagram illustrating an example of functions of an upflowprocessing unit;

FIG. 30 is a diagram illustrating an example of procedures of upflowprocessing;

FIG. 31 is a diagram illustrating an example of lower-order stackdetection information obtaining processing;

FIG. 32 is a flowchart illustrating an example of procedures oflower-order stack detection information obtaining processing;

FIG. 33 is a diagram illustrating an example of effect range searchingprocessing in an upflow;

FIG. 34 is a diagram illustrating an example of a stack operation modelin which lower-order stack detection information has been reflected;

FIG. 35 is a diagram illustrating an example of a stack operation modelin which search results of a range of effects in upflow processing havebeen reflected;

FIG. 36 is a flowchart illustrating an example of procedures of effectrange searching processing in upflow processing;

FIG. 37 is a diagram illustrating an example of search resultsnotification processing in upflow processing;

FIG. 38 is a flowchart illustrating an example of procedures of searchresults notification processing as to a higher-order stack;

FIG. 39 is a diagram illustrating an example of a failure effect rangedisplay screen;

FIG. 40 is a diagram illustrating an example of effect range searchprocessing in downflow processing according to a third embodiment;

FIG. 41 is a diagram illustrating an example of a stack operation modelin which there have been reflected search results of the range ofeffects in downflow processing according to a third embodiment;

FIG. 42 is a flowchart illustrating an example of range of effectssearch processing in downflow processing according to the thirdembodiment;

FIG. 43 is a diagram illustrating an example of search resultsnotification processing in downflow processing according to the thirdembodiment;

FIG. 44 is a diagram illustrating an example of effect range searchprocessing in an upflow in the third embodiment;

FIG. 45 is a diagram illustrating an example of a stack operation modelin which lower-order stack detection information according to the thirdembodiment has been reflected;

FIG. 46 is a diagram illustrating an example of a stack operation modelin which there have been reflected search results of the range ofeffects in upflow processing according to the third embodiment;

FIG. 47 is a flowchart illustrating an example of procedures of effectrange searching processing in upflow processing according to the thirdembodiment;

FIG. 48 is a diagram illustrating an example of search resultsnotification processing in upflow processing according to the thirdembodiment;

FIG. 49 is a diagram illustrating handover of information includingseriousness;

FIG. 50 is a diagram illustrating functions of a downflow processingunit in a fourth embodiment;

FIG. 51 is a diagram illustrating an example of stack operation modelaccording to the fourth embodiment;

FIG. 52 is a diagram illustrating an example of procedures of downflowprocessing according to the fourth embodiment;

FIG. 53 is a diagram illustrating an example of detection informationobtaining processing according to the fourth embodiment;

FIG. 54 is a diagram illustrating an example of a stack operation modelin which detection information according to the fourth embodiment isreflected;

FIG. 55 is a diagram illustrating an example of a stack operation modelin which are reflected search results of the range of effects indownflow processing according to the fourth embodiment;

FIG. 56 is a diagram illustrating an example of setting seriousness asto a stack operation model;

FIG. 57 is a flowchart illustrating an example of procedures ofseriousness calculation processing;

FIG. 58 is a diagram illustrating an example of search resultsnotification processing in downflow processing according to the fourthembodiment;

FIG. 59 is a diagram illustrating an example of a stack operation modelto which have been reflected search results of the range of effects inupflow processing according to the fourth embodiment;

FIG. 60 is a diagram illustrating an example of search resultsnotification processing in upflow processing according to the fourthembodiment;

FIG. 61 is a diagram illustrating an example of generating a stackoperation model for each failure effect range search;

FIG. 62 is a diagram illustrating an example of a cloud environmentincluding a stack regarding which an effect range identifying device hasnot been introduced; and

FIG. 63 is a diagram illustrating an example of a cloud environmentwhere multiple stacks run by different corporations exist in the samelayer.

DESCRIPTION OF EMBODIMENTS

A service (cloud service) using a cloud computing system has a layeredstructure where services are in multiple layers. For example, Platformas a Service (Paas) is provided by Infrastructure as a Service (IaaS)having been provided, and Software as a Service (SaaS) is provided byPaaS having been provided. In this case, each of IaaS, PaaS, and SaaS isa service layer. In such a cloud service, individual services providedat each layer are the object of judgement regarding whether or not it iswithin the range of effects of a failure.

In a case where services are in a multilayer structure, effects of afailure occurring at a service in a certain layer may propagate from thecertain layer to another layer. For example, a failure occurring in aservice at a certain layer may cause communication speed of a service inanother layer to drop. Accordingly, it is insufficient to search withinservices in a single layer to search for the range of effects of afailure.

However, searching of the range of effects of a failure in the relatedart has been performed on each layer separately, and searching of therange of effects of a failure is not performed across service layers.Accordingly, the range of effects of a failure is not accuratelycomprehended.

It is desirable to improve precision of identifying the range of effectsof failures.

Hereinafter, embodiments will be described with reference to thedrawings. It is understood that multiple embodiments may be combined andcarried out insofar as no conflict exists.

First Embodiment

FIG. 1 is a diagram illustrating an example of a system according to afirst embodiment. A cloud service provided using a cloud computingsystem 10 has a layered structure. The structure has three layers in theexample illustrated in FIG. 1. Each service layer will be assumed to bemanaged by a separate administrator. Description will primarily be madein the following regarding effect range identifying processing at thetime of a failure occurring, for the administrator of the service layerthat is the second layer from the top. Accordingly, with the servicelayer at the second layer from the top as a reference, the highest-orderservice layer will be referred to as higher-order service layer 11, theservice layer that is the second layer from the top will be referred asobject service layer 12, and the lowest-order service layer will bereferred to as lower-order service layer 13.

The higher-order service layer 11 is a service layer that provides SaaS,for example, the higher-order service layer 11 provides multiplehigher-order services 11 a, 11 b, and 11 c. The higher-order services 11a and 11 c are services provided using services 12 a and 12 c within theobject service layer 12. The higher-order service 11 b is a serviceprovided using lower-order service 13 a within the lower-order servicelayer 13. The higher-order services 11 a, 11 b, and 11 c are servicesprovided users with an application software usage environment, forexample. The identifier of the higher-order service 11 a is “App_a”, theidentifier of the higher-order service 11 b is “App_b”, and theidentifier of the higher-order service 11 c is “App_c”.

The object service layer 12 is a service layer providing PaaS, forexample. Multiple services 12 a, 12 b, and 12 c are provided at theobject service layer 12. The services 12 a, 12 b, and 12 c are servicesprovided using lower-order services 13 a, 13 b, and 13 d in thelower-order service layer 13. The services 12 a, 12 b, and 12 c areservices that provide users with a usage environment of software such asan application server, database, or the like, for example. Theidentifier of the service 12 a is “server A”, the identifier of theservice 12 b is “DB_A”, and the identifier of the service 12 c is“server B”.

The lower-order service layer 13 is a service layer that provides IaaS,for example. Multiple lower-order services 13 a, 13 b, 13 c, and 13 dare provided at the lower-order service layer 13. The lower-orderservices 13 a, 13 b, 13 c, and 13 d are services providing user with ausage environment of storage including virtual machines (VM) andRedundant Arrays of Inexpensive Disks (RAID) and so forth. Theidentifier of the lower-order service 13 a is “VM_α”, the identifier ofthe lower-order service 13 b is “VM_β”, the identifier of thelower-order service 13 c is “RAID”, and the identifier of thelower-order service 13 d is “VM_γ”. The lower-order service 13 c isprovided via the lower-order service 13 b or lower-order service 13 d.

In a case where a failure occurs on the cloud computing system 10,services that are in the range of effects of the failure are identifiedby an effect range identifying device corresponding to each servicelayer. Services within the range of effects of failure within thehigher-order service layer 11 are identified by higher-order effectrange identifying device 1. Services within the range of effects offailure within the object service layer 12 are identified by an effectrange identifying device 2. Services within the range of effects offailure within the lower-order service layer 13 are identified by alower-order effect range identifying device 3.

The higher-order effect range identifying device 1, effect rangeidentifying device 2, and lower-order effect range identifying device 3are realized by computers having a processor and memory, for example.The effect range identifying device 2 has a storage unit 2 a and aprocessing unit 2 b, for example. The storage unit 2 a is, for example,memory or a storage device that the effect range identifying device 2has. The processing unit 2 b is a processor or computing circuit thatthe effect range identifying device 2 has, for example.

The storage unit 2 a of the effect range identifying device 2 storessearch route information 2 aa indicating a search route for searchingfor services within the range of effects of a failure from a startpoint. The search route information 2 aa indicates search routes inaccordance with the type of start point service and the contents of thefailure.

The processing unit 2 b of the effect range identifying device 2references the search route information 2 aa in a case where a failurehas occurred within the cloud computing system 10, and identifiesservices within the range of effects of the failure within the objectservice layer 12.

In a case where a failure has been detected in a service layer otherthan the object service layer 12, the effect range identifying device 2recognizes the occurrence of the failure by information obtained fromthe higher-order effect range identifying device 1 or the lower-ordereffect range identifying device 3. For example, in a case where afailure is detected at the higher-order service 11 b within thehigher-order service layer 11, higher-order services within the range ofeffects of the failure (detected higher-order services) are identifiedby the higher-order effect range identifying device 1. The higher-ordereffect range identifying device 1 transmits identifiers of the detectedhigher-order services that have been detected, to the effect rangeidentifying device 2. The effect range identifying device 2 recognizesoccurrence of the failure within the cloud computing system 10 byreceiving the identifiers of the detected higher-order services. Theprocessing unit 2 b then searches the range of effects of the failure.

For example, the processing unit 2 b receives identifiers of thedetected higher-order services, regarding which occurrence of anabnormality or the possibility of being affected by the abnormality hasbeen detected, from the higher-order effect range identifying device 1.The processing unit 2 b then searches the range of effects based on thesearch route information 2 aa. That is to say, the processing unit 2 bsearches services within the object service layer that may be reached bytracing relations among services from the detected higher-orderservices, following a search route in a case where a detectedhigher-order service is a start point. The processing unit 2 b judgesservices which were successfully reached by the search as being firstin-effect-range services, where there is a possibility of being affectedby the abnormality. The processing unit 2 b then transmits theidentifiers of the first in-effect-range services to the lower-ordereffect range identifying device 3.

The lower-order effect range identifying device 3 identifies, out of thelower-order services 13 a through 13 d within the lower-order servicelayer 13, the lower-order services within the range of effects of thefailure, based on the identifiers of the first in-effect-range services.The lower-order effect range identifying device 3 transmits theidentifiers of services within the object service layer 12 usinglower-order services determined to be within the range of effects in therange of effects of failure search (using services) to the effect rangeidentifying device 2.

The processing unit 2 b of the effect range identifying device 2 obtainsthe identifiers of using services sent from the lower-order effect rangeidentifying device 3. Next, the processing unit 2 b searches forservices within the range of effects of the failure, based on the searchroute information 2 aa. The processing unit 2 b judges services withinthe effect object service layer that may be reached by tracing relationsamong services from using services, following a search route in a casewhere a using service is a start point service, as being secondin-effect-range service regarding which there is a possibility of beingaffected by the failure. The processing unit 2 b then transmitsidentifiers of higher-order services using the second in-effect-rangeservices, out of the higher-order services 11 a through 11 c within thehigher-order service layer 11, to the higher-order effect rangeidentifying device 1.

The higher-order effect range identifying device 1 recognizes that thereis a possibility of these higher-order services being affected by thefailure, based on the identifiers of the used higher-order services.

According to this flow, services within the range of effects of thefailure may be identified while taking into consideration propagation ofeffects of the failure over multiple service layers, by the higher-ordereffect range identifying device 1, effect range identifying device 2,and lower-order effect range identifying device 3 performing cooperativeprocessing. This improves the precision of identifying services withinthe range of effects of the failure.

For example, assumption will be made that a failure is detected at thehigher-order service 11 b. In this case, the higher-order effect rangeidentifying device 1 searches for higher-order services within the rangeof effects of the failure, with the higher-order service 11 b as thestart point service. In the example in FIG. 1, the higher-order service11 a is detected as being within the range of effects of the failure. Inresponse to this, the higher-order effect range identifying device 1transmits the identifiers “App_a, App_b” of the detected higher-orderservices to the effect range identifying device 2.

The processing unit 2 b of the effect range identifying device 2 obtainsthe identifiers “App_a, App_b” of the detected higher-order services.The processing unit 2 b then searches the range of effects with each ofthe detected higher-order services as a start point. In the example inFIG. 1, the services 12 a and 12 b are identified as being serviceswithin the range of effects (services within first range of effects).Next, the processing unit 2 b transmits the identifiers “server A, DB_A)of the first in-effect-range services to the lower-order effect rangeidentifying device 3.

The lower-order effect range identifying device 3 searches for serviceswithin the range of effects of the lower-order service layer 13, witheach of the first in-effect-range services as a start point. In theexample in FIG. 1, the lower-order services 13 a through 13 d areidentified as being within the range of effects. The lower-order effectrange identifying device 3 then transmits the identifiers “server A,DB_A, server B” of the services within the object service layer 12 usingthe lower-order services 13 a through 13 d that have been identified(using services) to the effect range identifying device 2.

Upon receiving the identifiers “server A, DB_A, server B” of the usingservices, the processing unit 2 b of the effect range identifying device2 searches for the range of effects of failure with each using serviceas a start point. In the example in FIG. 1, services 12 a through 12 care judged to be services within the range of effects of the failure(services within second range of effects). The processing unit 2 btransmits the identifiers “App_a, App_c” of higher-order services withinthe higher-order service layer 11 using the second in-effect-rangeservices (using higher-order services) to the higher-order effect rangeidentifying device 1.

Thus, the administrator of the object service layer 12 may accuratelycomprehend the effects of the failure detected at the higher-orderservice layer 11 on the object service layer 12, by confirming thesearch results of the range of effects by the effect range identifyingdevice 2, for example.

Note that the effect range identifying device 2 may display the searchresults of the range of effects of failure on a terminal device that theadministrator uses. For example, the processing unit 2 b of the effectrange identifying device 2 outputs display data indicating servicesidentified to be within the range of effects of failure in the objectservice layer 12 (services within the first or second range of effects)to the terminal device used by the administrator. Thus, theadministrator may readily confirm the results of search of the range ofeffects.

Note that in a case where there are multiple detected higher-orderservices, the processing unit 2 b of the effect range identifying device2 judges first in-effect-range services with each of the multipledetected higher-order services as a start point service. The processingunit 2 b then decides a value corresponding the number of times thatjudgement has been made that a first in-effect-range service may bereached by tracing relations among services from a detected higher-orderservice, as being a severity of the failure for that firstin-effect-range service. In a case of having decided a severity, theprocessing unit 2 b displays severity display data on the terminaldevice used by the administrator, to display the severity of each of thefirst and second in-effect-range services within the object servicelayer 12. Thus, the difference among probabilities of being affected maybe compared among the multiple services that will be affected by thefailure, and the administrator may handle the failure with priorityregarding services that have a higher probability of being affected. Asa result, the effects of the failure may be efficiently suppressed fromspreading.

Further, the processing unit 2 b of the effect range identifying device2 may calculate the seriousness of a case of the first and secondin-effect-range services being affected by the failure, based on theusage forms of the first and second in-effect-range services. In thiscase, the processing unit 2 b outputs seriousness display data fordisplaying the seriousness of the first and second in-effect-rangeservices within the object service layer 12 to the terminal device thatthe administrator uses. Accordingly, the difference among theseriousness of being affected may be compared among the multipleservices in a case of being affected by the failure, and theadministrator may take measures to deal with the failure with priorityregarding services that have a higher probability of being affected. Asa result, reduced service quality due to effects of the failureseriously affecting business operations of users of the service may besuppressed.

Note that when calculating the seriousness, the processing unit 2 b mayreflect the usage form of higher-order services within the higher-orderservice layer 11 that use the first and second in-effect-range services,in the seriousness for example. For example, the processing unit 2 badds a value calculated based on the usage form of the first and secondin-effect-range services, and a value calculated based on the usage formof higher-order services within the higher-order service layer that usethe first in-effect-range services. The processing unit 2 b then sets avalue, obtained by adding the values obtained for each of the first andsecond in-effect-range services, as the seriousness of each of the firstand second in-effect-range services. Thus, seriousness may be calculatedtaking into consideration the usage stage of services in service layersmanaged by other administrators, and seriousness with higher reliabilitymay be calculated.

Second Embodiment

Next, a second embodiment will be described. The second embodimentinvolves searching for the range of effects of failure in a cloudservice where IaaS, PaaS, and SaaS are provided in a layered structure.

FIG. 2 is a diagram illustrating a system configuration exampleaccording to the second embodiment. Multiple servers 100, 100 a, and soforth, are provided in a cloud computing system 20. The multiple servers100, 100 a, and so forth, provide various cloud services. Multipleterminal devices 31, 32, and so forth, are connected to the cloudcomputing system 20 via a network. Users use the terminal devices 31,32, and so forth, to access the cloud computing system 20 and receiveproviding of cloud services.

FIG. 3 is a diagram illustrating a configuration of server hardware. Theentire server 100 is controlled by a processor 101. Memory 102 andmultiple peripheral devices are connected to the processor 101 via a bus109. The processor 101 may be a multiprocessor. Examples of theprocessor 101 include a central processing unit (CPU), micro processingunit (MPU) and digital signal processor (DSP). At least part offunctions realized by the processor 101 executing a program may berealized by an electronic circuit such as an application specificintegrated circuit (ASIC), programmable logic device (PLD), or the like.

The memory 102 is used as a main storage device for the server 100. Thememory 102 temporarily stores at least part of an operating system (OS)program and application programs to be executed by the processor 101.The memory 102 also stores various types of data to be used forprocessing by the processor 101. A volatile semiconductor device such asrandom access memory (RAM), for example, is used for the memory 102.

Peripheral devices connected to the bus 109 include a storage device103, graphics processing device 104, input interface 105, optical drivedevice 106, device connection interface 107, and network interface 108.

The storage device 103 electrically or magnetically writes and readsdata to and from a built-in storage medium. The storage device 103 isused as an auxiliary storage device of the computer. The storage device103 stores OS programs, application programs, and various types of data.Examples of the storage device 103 include a hard disk drive HDD and asolid state drive (SSD).

A monitor 21 is connected to the graphics processing device 104. Thegraphics processing device 104 displays images on a screen of themonitor 21 in accordance with commands from the processor 101. Examplesof the monitor 21 include organic electroluminescence display devices,liquid crystal display devices, and so forth.

A keyboard 22 and mouse 23 are connected to the input interface 105. Theinput interface 105 transmits signals sent from the keyboard 22 andmouse 23 to the processor 101. Note that the mouse 23 is an example of apointing device, and that other pointing devices may also be used.Examples of other point devices include a touch panel, tablet, touchpad,trackball, and so forth.

The optical drive device 106 reads data recorded in an optical disc 24,using laser beams or the like. An optical disc 24 is a portablerecording medium in which data has been recorded so as to be able to beread using reflection of light. Examples of an optical disc 24 includedigital versatile disc (DVD), DVD-RAM, compact disc read only memory(CD-ROM), CD-recordable (CD-R)/rewritable (RW), and so forth.

The device connection interface 107 is a communication information forconnecting peripheral devices to the server 100. For example, a memorydevice 25 and memory reader/writer 26 may be connected to the deviceconnection interface 107. The memory device 25 is a recording mediumhaving functions of communication with the device connection interface107. The memory reader/writer 26 is a device that writes data to amemory card 27, and also reads data from the memory card 27. The memorycard 27 is a card-type recording medium.

The network interface 108 is connected to a network 20 a within thecloud computing system 20. The network interface 108 exchanges data withother computers and communication equipment via the network 20 a.

The processing functions of the second embodiment may be realized by theabove hardware configuration. Note that the effect range identifyingdevices 1 through 3 described in the first embodiment may also berealized by hardware the same as the server 100 illustrated in FIG. 3.

The server 100 realizes the processing functions of the secondembodiment by executing programs recorded in a computer-readablerecording medium, for example. Programs describing the processingcontents to be executed by the server 100 may be stored in various typesof recording media. For example, programs to be executed by the server100 may be stored in the storage device 103. The processor 101 loads atleast part of programs in the storage device 103 to the memory 102, andexecutes the programs. Also, programs to be executed by the server 100may be recorded in portable recording media, such as the optical disc24, memory device 25, memory card 27, or the like. Programs stored inportable recording media are executable after having been installed tothe storage device 103 under control of the processor 101, for example.Alternatively, the processor 101 may also read out programs directlyfrom portable recording media, and execute.

Next, a layered structure of a cloud service will be described.

FIG. 4 is a diagram illustrating an example of a cloud service. Thecloud service has a layered structure of IaaS providing infrastructure,PaaS providing platforms, and SaaS providing applications, for example.The layers of the cloud service will be referred to as stacks 51 through53 below.

In the stack 51 that is IaaS, a usage environment of virtual machines(VMs) 51 a, 51 b, and 51 c is provided. A user that uses a terminaldevice 31 in the example in FIG. 4 has configured a customer system 41on the VM 51 a, and is operating the customer system 41. In the sameway, a user that uses a terminal device 32 has configured a customersystem 42 on the VM 51 b, and is operating the customer system 42. Thecustomer systems 41 and 42 include a platform on which applicationsoftware (hereinafter referred to simply as “application”) is run, andapplications on the platform. The platform includes OS, various types ofmiddleware, databases, and so forth.

A user using the VM 51 c provides services at the PaaS stack 52 usingthe VM 51 c. The stack 52 includes platforms 52 a and 52 b. A user usinga terminal device 33 introduces a customer application 43 on theplatform 52 a, and uses the customer application 43 using the terminaldevice 33. A user using a terminal device 34 introduces a customerapplication 44 on the platform 52 b, and uses the customer application44 using the terminal device 34.

In the example in FIG. 4, service at the stack 53 that is SaaS isprovided using the platform 52 b. A usage environment of applications 53a and 53 b as a service is provided at the stack 53. A user using aterminal device 35 uses an application 53 a provided at the stack 53. Auser using a terminal device 36 uses an application 53 b provided at thestack 53, by using the terminal device 36.

Thus, when multiple stacks are in layers, there are cases where eachstack is provided and managed by separate corporations. Also, even ifstacks in different layers are provided by the same corporation, thestacks may each be provided and managed by separate divisions in thecorporation. For example, monitoring devices 61 through 63 that arerealized by VMs are provided in the respective stacks. The monitoringdevices 61 through 63 monitor operations of services within the stackthey belong to, and if there is an abnormality in operations, detectsthat abnormality.

The monitoring devices 61 through 63 perform monitoring for eachprovided service. Functions of provided services that are the object ofmonitoring may be handled on the system in the same way as equipmenthaving the functions. Accordingly, increments of services that are theobject of monitoring will be referred to as “equipment” in the followingdescription. For example, the VMs 51 a, 51 b, 51 c, the platforms 52 aand 52 b, and the applications 53 a and 53 b each are equipment that isthe object of monitoring.

Further, effect range identifying devices 200, 300 and 400 realized byVMs, for example, are provided at the respective stacks. The effectrange identifying devices 200, 300 and 400 obtain information ofequipment where a failure has occurred, from the monitoring devices 61through 63 of the respective stacks to which they belong to. Effectsthat a failure that has occurred are searched over multiple differentstacks by the multiple effect range identifying devices 200, 300 and 400operating in cooperation.

Now, before describing details of the effect range searching processingperformed by the effect range identifying devices 200, 300 and 400,problems that occur when the effect range identifying devices 200, 300and 400 are not in cooperation will be described.

In a cloud environment where multiple stacks such as IaaS, PaaS, andSaaS are connected in layers, as illustrated in FIG. 4, in a case wherea failure has occurred at a part of equipment of the system, the failureis propagated over the stacks. However, the providers of the stacks arenot able to inform each other of configuration information of the systemthat each one is managing, or customer information (types of businesswhere occurrence of trouble would have great social impact, the numberof customers that each has, and so forth), from the perspective ofprotecting personal information and keeping trade secrets. The onlyinformation that the providers of each stack may know is equipment(equipment of a higher-order stack) that uses the equipment (equipmentmaking up the system, such as physical equipment, virtual equipment andsoftware, network equipment, and so forth) managed by him/herself.Accordingly, the administrator of a stack is not able to comprehend therelation of connection among equipment at stacks other than the stack(higher-order stacks or lower-order stacks) managed by him/herself, orthe relation of connection among stacks other than the stack managed byhim/herself. As a result, the administrators of each stack are not ableto view the entire system comprehensively and trace the propagation ofthe failure, and are not able to analyze the range of effects of afailure or estimate the cause of the failure.

Accordingly, in the second embodiment, the effect range identifyingdevices 200, 300 and 400 are provided to the respective stacks, and theeffect range identifying devices 200, 300 and 400 are operatedcooperatively, thereby enabling searching for the range of effects offailure over multiple stacks.

FIG. 5 is a diagram illustrating transmission paths of information amongeffect range identifying devices. The stacks 51 through 53 may knowinformation of stacks on the higher-order side of itself. Accordingly,information of connection between a higher-order stack and a lower-orderstack is managed by an effect range identifying device of thelower-order stack. For example, information of connection betweenequipment within the stack 53 (higher-order side) and equipment withinthe stack 52 (lower-order side) is managed at the effect rangeidentifying device 300 at the lower-order stack 52.

In a case where a failure occurs, the effect range identifying devices200, 300 and 400 exchange information, and search for the range ofeffects of the failure. The information that is exchanged is identifiersof equipment regarding which a failure has been detected(failure-detected equipment), and identifiers of equipment that may beaffected by the failure (failure-affected equipment). For example, theeffect range identifying device within a higher-order stack transmitsthe identifiers of equipment where failure has occurred andfailure-affected equipment within the stack to which it belongs, toeffect range identifying devices at lower-order stacks. The effect rangeidentifying devices within a lower-order stack transmits identifiers ofequipment within the higher-order stack to which failure-affectedequipment within its own stack are connected, to the effect rangeidentifying devices in higher-order stacks.

The effect range identifying devices 200, 300 and 400 within the stacks51 through 53 search for the range of effects of failure within theirown stacks, and transmit the search results to the effect rangeidentifying devices of the other stacks.

For example, in a case where a failure is detected at equipment withinthe stack 53, the effect range identifying device 200 searches forwithin the range of effects of failure (failure-affected equipment)within the stack 53, and notifies the effect range identifying device300 within the stack 52 of the identifiers of the failure-detectedequipment and failure-affected equipment. The effect range identifyingdevice 300 searches for the range of effects of failure, with theequipment within the stack 52 connected to the failure-detectedequipment and failure-affected equipment regarding which notificationhas been made, as a start point, and identifies failure-affectedequipment within the stack 52. The effect range identifying device 300then notifies the effect range identifying device 400 of the lower-orderstack 51 of the identifiers of the failure-affected equipment within thestack 52. The effect range identifying device 400 searches for the rangeof effects of failure, with the equipment within the stack 51 connectedto the failure-affected equipment regarding which notification has beenmade, as a start point, and identifies failure-affected equipment withinthe stack 51.

The effect range identifying device 400 within the lowest-order stack 51notifies the effect range identifying device 300 of the stack 52 of theidentifiers of equipment in the higher-order stack 52 connected to thefailure-affected equipment within the stack 51. The effect rangeidentifying device 300 searches for the range of effects of failure withthe equipment regarding which notification has been made as a startpoint, and identifies failure-affected equipment within the stack 52.The effect range identifying device 300 then notifies the effect rangeidentifying device 200 of the higher-order stack 53 of identifiers ofthe equipment of the higher-order stack 53 connected to thefailure-affected equipment within the stack 52.

Thus, upon information being transmitted from the effect rangeidentifying device of a higher-order stack to the effect rangeidentifying device of a lower-order stack, and information beingtransmitted to the effect range identifying device of the lowest-orderstack, information is transmitted from that stack in order tohigher-order stacks. Hereinafter, transmission of information from theeffect range identifying device of a higher-order stack to the effectrange identifying device of a lower-order stack will be referred to asdownflow, and transmission of information from the effect rangeidentifying device of a lower-order stack to the effect rangeidentifying device of a higher-order stack will be referred to asupflow.

Next, the functions of the effect range identifying devices 200, 300,and 400 will be described.

FIG. 6 is a block diagram illustrating an example of functions of aneffect range identifying device. Although FIG. 6 illustrates thefunctions of the effect range identifying device 300, the functions ofthe other effect range identifying devices 200 and 400 are also the sameas those of the effect range identifying device 300.

The effect range identifying device 300 includes an effect range searchroute information storage unit 310, a stack operation model storage unit320, a stack information managing unit 330, a downflow processing unit340, and an upflow processing unit 350.

The effect range search route information storage unit 310 stores effectrange search route information indicating a search route of the range ofeffects of failure from equipment serving as a start point.

The stack operation model storage unit 320 stores a stack operationmodel indicating the range of effects of failure of each piece ofequipment when a failure occurs. The stack information managing unit 330manages identification numbers of the stack 52 to which the effect rangeidentifying device 300 belongs, and of the higher and lower stacks 51and 53. The downflow processing unit 340 performs downflow processingthat is transmission information from a higher-order stack to alower-order stack. The upflow processing unit 350 performs upflowprocessing that is transmission information from a lower-order stack toa higher-order stack. The downflow processing unit 340 and upflowprocessing unit 350 also may display information relating tofailure-affected equipment within the stack 52 on the terminal device 30used by the administrator.

Note that the lines connecting the components illustrated in FIG. 6 onlyillustrate part of communication paths, and that communication pathsother than the illustrated communication paths may be set. The functionsof the components illustrated in FIG. 6 may be realized by causing acomputer to execute program modules corresponding to the components.

FIG. 7 is a diagram illustrating an example of an effect range searchroute information storage unit. The effect range search routeinformation storage unit 310 stores effect range search routeinformation 311. The effect range search route information 311 includesfailure and search route correlation table 311 a indicating searchroutes within the stack, failure and search route correlation table 311b indicating search routes over multiple stacks, and search routeinformation 311 c.

The failure and search route correlation table 311 a has search routenumbers that uniquely indicate search routes set corresponding to setsof functions of equipment within each stack and failure types. A failuretype is a type of resource that may be a cause of a failure, such as adisk-related failure or a CPU-related failure, for example.

The failure and search route correlation table 311 b has search routenumbers that uniquely indicate search routes set corresponding to setsof functions of equipment and failure types, for each set of stack towhich the equipment serving as a start point belongs, and a high-orderor lower-order stack as to that stack.

The search route information 311 c indicates a search route for eachsearch route number, corresponding to that search route number. A searchroute is indicated by the layout of functions of equipment regardingwhich the range of effects is searched. For example, a search routeindicated by “search route #1” is “VM→data storage→RAID datastorage→VM”. This search route indicates that the search starts fromequipment of which the function is “VM”. This also indicates thatequipment that is connected to the “VM” equipment and of which thefunction is “data storage” is to be searched next. In a case whererelevant equipment is successfully detected, equipment havingcorresponding functions are searched for from equipment connected to theequipment detected last, in the order indicated by the search route.

An example of search routes will be described with reference to FIG. 8.

FIG. 8 is a diagram illustrating an example of search routes. FIG. 8illustrates “search route #1”, “search route #2”, “search route #11”,and “search route #21”, as intra-stack search routes.

The “search route #1” within IaaS is one where the cause of failure isdisk-related, and is applied in a case where the start point equipmentis a VM. In a case where “search route #1” is applied at the time of arange of effects search within IaaS, searching for adjacent equipment(equipment having a connection relation) having the relevant functionsis performed in the order of “VM→data storage→RAID data storage→VM”.

The “search route #2” within IaaS is one where the cause of failure isCPU-related, and is applied in a case where the start point equipment isa VM. In a case where “search route #2” is applied at the time of arange of effects search within IaaS, searching for adjacent equipmenthaving the relevant functions is performed in the order of“VM→hypervisor (HV)→VM”.

The “search route #11” within PaaS is applied in a case where the startpoint equipment is Web application, for all causes of failure. In a casewhere “search route #11” is applied at the time of a range of effectssearch within PaaS, searching for adjacent equipment having the relevantfunctions is performed in the order of “Web application→database(DB)→Web application”.

The “search route #21” within SaaS is applied in a case where the startpoint equipment is an application, for all causes of failure. In a casewhere “search route #21” is applied at the time of a range of effectssearch within SaaS, searching for adjacent equipment having the relevantfunctions is performed in the order of “application→application”.

FIG. 8 also illustrates “search route #31”, “search route #41”, and“search route #51” as inter-stack search routes.

The “search route #31” for PaaS→IaaS is one where the cause of failureis disk-related, and is applied in a case where the start pointequipment is a database in the higher-order stack. In a case where“search route #31” is applied at the time of a range of effects searchwithin IaaS, searching for adjacent equipment having the relevantfunctions is performed from a VM in the IaaS on which the databaseserving as the start point is dependent, in the same order as the“search route #1”. Note that the meaning of equipment A being dependenton equipment B is that equipment A is being executed using the functionsof equipment B (VM, OS, middleware, or the like) as an executionplatform.

The “search route #41” for SaaS PaaS is applied in a case where thestart point equipment is a SaaS application, for all causes of failure.In a case where “search route #41” is applied at the time of a range ofeffects search within PaaS of which the start point is equipment withinSaaS, dependent equipment is searched for from the platform on which thestart point application is dependent (“zzz” in the example in FIG. 8).In a case where equipment on which the platform “zzz” that the startpoint application is dependent on is not in the same stack as “zzz”,just “zzz” is the equipment within the range of effects.

The “search route #51” for IaaS PaaS is one where the start point is aVM of the IaaS, for all causes of failure. In a case where “search route#51” is applied at the time of a range of effects search within PaaS ofwhich the start point is equipment within IaaS, from the databasedependent on the VM that is the start point to all Web applicationsdependent on the database, are equipment within the range of effects.

Next, an example of a stack operation model stored in the stackoperation model storage unit 320 will be described.

FIG. 9 is a diagram illustrating an example of a stack operation model.A stack operation model 321 includes equipment information andconnection relation information. Equipment information has set therein,in correlation with identifiers of each equipment of stack 52 and thehigher-order stack 53, function of the equipment, identifier of thestack to which the equipment belongs (stack No.), information indicatingwhether or not a failure has occurred (value of the column “occurrenceof failure”), and information indicating whether or not there areeffects of failure (value of the column “effects of failure”).

The type of the stack to which the equipment belongs (IaaS, PaaS, SaaS)is given as the function of the equipment. The function of the equipmentincludes information indicating a specific service type, such asdatabase, VM, and so forth, although omitted from illustration in FIG.9.

In a case where the corresponding equipment is failure-detectedequipment, for example, information indicating whether or not a failurehas occurred is set to the value “1” indicating that a failure hasoccurred. In a case where the corresponding equipment isfailure-affected equipment, for example, information indicating whetheror not there are effects of failure is set to the value “1” indicatingthat this is within the range of effects of failure.

The connection relation information indicates the connection relationamong equipment within the stack 52, and the connection relation betweenequipment within stack 52 and equipment within stack 53. The connectionrelation among equipment within the stack 52 is the relation between twopieces of equipment that operate cooperatively to provide a service, orthe relation between two pieces of equipment where one piece ofequipment is dependent on the other piece of equipment. The connectionrelation between equipment within stack 52 and equipment within stack 53is the relation between equipment within the stack 52, and the equipmentwithin the higher-order stack 53 that is dependent on that equipment.

Next, functions of the stack information managing unit 330 will bedescribed.

FIG. 10 is a diagram illustrating an example of the functions of thestack information managing unit 330. The stack information managing unit330 includes a stack information storage unit 331, a stack No.generating unit 332, an own stack No. notification unit 333, and a stackNo. transmission/reception unit 334.

The stack information storage unit 331 stores the stack No. of the stack52 (Paas) to which it belongs, the stack No. of the lower-order stack 51(IaaS), and the stack No. of the higher-order stack 53 (SaaS).

The stack No. generating unit 332 generates the stack No. of the stack52. The own stack No. notification unit 333 transmits its own stack No.to the effect range identifying device 400 of the lower-order stack 51.The stack No. transmission/reception unit 334 obtains the stack Nos. ofthe lower-order stack 51 and the higher-order stack 53.

The procedures for own stack No. registration processing by the stackNo. generating unit 332 and own stack No. notification unit 333 will bedescribed below with reference to FIGS. 11 and 12.

FIG. 11 is a flowchart illustrating an example of procedures of the ownstack No. registration processing. Description will be made of theprocessing illustrated in FIG. 11 following the step numbers.

(Step S101) The stack No. generating unit 332 generates a stack No. forits own stack. For example, when the effect range identifying device 300is introduced to the stack 52 (when software for the effect rangeidentifying device 300 is installed to the VM for the stack 52), thestack No. generating unit 332 generates a unique stack No. An example ofa unique stack No. is a number including identifiers of all stacks ofthe entire system. A unique number may also be made by including in thestack No. the time at which the stack No. was generated.

(Step S102) The stack No. generating unit 332 stores the generated stackNo. in the stack information storage unit 331 as the stack No. of thestack 52. The stack No. generating unit 332 also transmits the generatedstack No. to the own stack No. notification unit 333.

(Step S103) The own stack No. notification unit 333 transmits theobtained stack No. to the effect range identifying device 400 of thelower-order stack 51.

FIG. 12 is a diagram illustrating an example of the results of own stackNo. registration processing. The stack No. generated at the stack No.generating unit 332 is stored in the stack information storage unit 331within the stack information managing unit 330 as the stack No. of itsown stack, as illustrated in FIG. 12. The generated stack No. of the ownstack is also transmitted to the effect range identifying device 400within the lower-order stack 51.

At the effect range identifying device 400, the stack No. of the ownstack that is transmitted thereto is stored as the stack No. of thehigher-order stack. As a result, the presence of the effect rangeidentifying device 300 introduced to the stack 52 is recognized by theeffect range identifying device 400 within the lower-order stack 51.

Next, the procedures of other stack No. registration processing by thestack No. transmission/reception unit 334 will be described withreference to FIGS. 13 and 14.

FIG. 13 is a flowchart illustrating an example of the procedures ofother stack No. registration processing. The processing illustrated inFIG. 13 will be described below following the step numbers.

(Step S111) The stack No. transmission/reception unit 334 obtains thestack No. of the lower-order stack 51, from the effect range identifyingdevice 400 within the lower-order stack 51.

(Step S112) The stack No. transmission/reception unit 334 stores theobtained stack No. in the stack information storage unit 331 as alower-order stack No.

(Step S113) The stack No. transmission/reception unit 334 obtains itsown stack No. from the stack information storage unit 331, and transmitsits own stack No. to the effect range identifying device 200 within thehigher-order stack 53.

(Step S114) The stack No. transmission/reception unit 334 obtains thestack No. of the higher-order stack 53 from the effect range identifyingdevice 200 within the higher-order stack 53.

(Step S115) The stack No. transmission/reception unit 334 stores theobtained stack No. in the stack information storage unit 331 as thehigher-order stack No.

(Step S116) The stack No. transmission/reception unit 334 stores thestack information (stack Nos. of the stacks) stored in the stackinformation storage unit 331, in a system configuration informationstorage unit 341 within the downflow processing unit 340. Accordingly,the downflow processing unit 340 may recognize the higher-order andlower-order effect range identifying devices 200 and 400 within thehigher-order and lower-order stacks by their stack Nos. Thereafter theseries of processing of stack information management (processing at thetime of introducing effect range identifying device) ends.

Note that the other stack No. registration processing may end at thepoint of having notified the higher-order stack 53 of the stack No. ofthe stack 52. In this case, the stack No. transmission/reception unit334 obtains the stack No. of the higher-order stack 53 when searchingeffects of failure, and stores the obtained stack No. in the stackinformation storage unit 331 and also stores in the system configurationinformation storage unit 341.

FIG. 14 is a diagram illustrating an example of results of other stackNo. registration processing. The stack No. obtained from the effectrange identifying device 400 in the lower-order stack 51 is stored inthe stack information managing unit 330 as a lower-order stack No., asillustrated in FIG. 14. Also, the stack No. obtained from the effectrange identifying device 200 within the higher-order stack 53 is storedin the stack information managing unit 330 as a higher-order stack No.The stack Nos. stored in the stack information storage unit 331 are alsostored in the system configuration information storage unit 341 of thedownflow processing unit 340.

Thus, in a case where the effect range identifying device 300 isintroduced to the stack 52, the stack information managing unit 330exchanges stack Nos. with the effect range identifying devices 200 and400 of the higher-order stack 53 and lower-order stack 51. Accordingly,the effect range identifying device among stacks of different layers mayidentify each other.

Next, details of downflow processing will be described.

FIG. 15 is a diagram illustrating an example of function in a downflowprocessing unit. The downflow processing unit 340 includes the systemconfiguration information storage unit 341, a detection informationobtaining unit 342, an information collecting unit 343, an effectssearching unit 344, and a search results notifying unit 345.

The system configuration information storage unit 341 stores connectioninformation of equipment within the higher-order stack 53 and equipmentwithin the stack 52, and system configuration information of the stack52. The connection information of equipment within the higher-orderstack 53 and equipment within the stack 52 includes sets of anidentifier of equipment within the stack 52, and an identifier ofequipment within the higher-order stack 53 that is operating dependentlyon that equipment. The system configuration information of the stack 52includes sets of identifiers of two pieces of equipment operating incooperation, among the equipment within the stack 52.

The detection information obtaining unit 342 obtains informationindicating failure-detected equipment and failure-affected equipmentfrom the effect range identifying device 200 of the higher-order stack53 (higher-order stack detection information). The detection informationobtaining unit 342 also obtains information indicating failure-detectedequipment from a monitoring device 62 within the stack 52 (own stackdetection information). The information collecting unit 343 creates astack operation model based on the information within the systemconfiguration information storage unit 341. The effects searching unit344 searches for the range of effects of failure, with afailure-detected equipment or failure-affected equipment as a startpoint. The search results notifying unit 345 transmits information ofthe failure-detected equipment and failure-affected equipment detectedin the stack 52 to the effect range identifying device 400 of thelower-order stack 51. The search results notifying unit 345 alsonotifies the terminal device 30 that the administrator of the stack 52uses, regarding the range of effects of the failure.

In a case of the downflow processing unit 340 having detected that afailure has occurred somewhere in the cloud computing system 20,downflow processing is started. For example, the downflow processingunit 340 detects occurrence of a failure by receiving higher-order stackdetection information including the identifiers of failure-detectedequipment where a failure has occurred and failure-affected equipment,from the effect range identifying device 200 of the higher-order stack53. The downflow processing unit 340 also detects occurrence of afailure by receiving own stack detection information includingidentifiers of failure-detected equipment from the monitoring device 62.

FIG. 16 is a diagram illustrating an example of procedures of downflowprocessing. Description of the processing illustrated in FIG. 16 will bemade below following the step numbers.

(Step S201) The detection information obtaining unit 342 performsdetection information obtaining processing. Details of the detectioninformation obtaining processing will be described later (see FIG. 19).

(Step S202) The information collecting unit 343 performs informationcollection processing. A stack operation model is generated by theinformation collection processing. Details of the information collectionprocessing will be described later (see FIG. 21).

(Step S203) The effects searching unit 344 performs effect rangesearching processing. Details of the effect range searching processingwill be described later (see FIG. 25).

(Step S204) The search results notifying unit 345 performs processing tonotify the lower-order stack 51 of the search results. Details of theprocessing to notify the lower-order stack 51 of the search results willbe described later (see FIG. 27).

Downflow processing is executed by these procedures at the time ofhaving obtained higher-order stack detection information. Thehigher-order stack detection information is transmitted from the effectrange identifying device 200 of the higher-order stack 53 that hasdetected failure-detected equipment when a failure has occurred. Notethat equipment within the stack 52 may also be detected asfailure-detected equipment when a failure has occurred.

FIG. 17 is a diagram illustrating a detection example offailure-detected equipment and failure-affected equipment. In theexample in FIG. 17, detecting has been made that a failure has occurredat equipment “app_c” in the stack 53 and equipment “bb” in the stack 52.Note that occurrence of a failure in equipment in the stack 53 isdetected by a monitoring device 63, and the identifier of the equipmentat which the failure has occurred is notified from the monitoring device63 to the effect range identifying device 200 (see FIG. 4). Occurrenceof a failure at equipment within the stack 52 is detected by themonitoring device 62, and the identifier of the equipment at which thefailure has occurred is notified from the monitoring device 62 to theeffect range identifying device 300 (see FIG. 4).

In the example in FIG. 17, as a result of the effect range search by theeffect range identifying device 200 within the stack 53 with equipment“app_a” as a start point, equipment “app_a” and equipment “app_b” havebeen detected as being failure-affected equipment. In this case,higher-order stack detection information indicating failure-detectedequipment “app_c” and failure-affected equipment “app_a, app_b” istransmitted from the effect range identifying device 200 within thestack 53 to the effect range identifying device 300 within the stack 52.

FIG. 18 is a diagram illustrating an example of detection informationobtaining processing. The detection information obtaining unit 342obtains higher-order stack detection information 71 and own-stackdetection information 72, as illustrated in FIG. 18.

The higher-order stack detection information 71 has set, in correlationwith the identifier of equipment (equipment name) within thehigher-order stack 53, the stack No. of the stack to which the equipmentbelongs, information indicating whether or not a failure has occurred,and information of whether or not there are effects of a failure. Theinformation indicating whether or not a failure has occurred is set inthe “occurrence of failure” column, and information indicating whetheror not there are effects of failure is set in the “effects of failure”column. The value of the occurrence of failure column for the “app_c”that is the failure-detected equipment is “1”, and the value of theeffects of failure column is “0”. The value of the occurrence of failurecolumn is “0” for the “app_a” and “app_b” that are failure-affectedequipment, and the value of the effects of failure column is “1”.

In the own-stack detection information 72 are set, in correlation withthe identifier of equipment (equipment name) within the stack 52 towhich the effect range identifying device 300 belongs, the stack No. ofthe stack to which the equipment belongs, failure occurrenceinformation, and failure effects information. The value of the failureoccurrence column is “1” for the equipment “bb” that is afailure-detected equipment, and the value of the failure effects columnis “0”.

The detection information obtaining unit 342 generates detectioninformation 73 in which the higher-order stack detection information 71and own-stack detection information 72 have been integrated, andtransmits the generated detection information 73 to the effectssearching unit 344.

FIG. 19 is a flowchart illustrating an example of procedures fordetection information obtaining processing. The processing illustratedin FIG. 19 will be described below following the step numbers.

(Step S211) The detection information obtaining unit 342 obtains thehigher-order stack detection information 71 from the effect rangeidentifying device 200 within the higher-order stack 53.

(Step S212) The detection information obtaining unit 342 obtains theown-stack detection information 72 from the monitoring device 62 withinthe stack 52 to which the effect range identifying device 300 belongs.

(Step S213) The detection information obtaining unit 342 integrates thehigher-order stack detection information 71 and the own-stack detectioninformation 72. For example, the detection information obtaining unit342 generates new detection information 73 that includes records foreach piece of equipment within the higher-order stack detectioninformation 71, and records for each piece of equipment within theown-stack detection information 72.

(Step S214) The detection information obtaining unit 342 transmits thegenerated detection information 73 to the effects searching unit 344.

Thus, detection information 73 where the higher-order stack detectioninformation 71 and own-stack detection information 72 have beenintegrated is generated.

Next, information collecting processing will be described in detail.

FIG. 20 is a diagram illustrating an example of information collectingprocessing. The information collecting unit 343 generates a stackoperation model 321 based on information stored in the systemconfiguration information storage unit 341. For example, the systemconfiguration information storage unit 341 includes connectioninformation 341 a and system configuration information 341 b. Theconnection information 341 a includes information indicating theconnection relation of equipment within the stack 52, and connectioninformation between equipment in the stack 52 and equipment in thehigher-order stack 53. The system configuration information 341 b hasregistered therein equipment within the stacks 52 and 53. The equipmentillustrated in the system configuration information 341 b is impartedinformation indicating the equipment function (VM, Data storage, PaaS,SaaS, or the like).

The information collecting unit 343 obtains the identifiers of equipmentmaking up the system of the stack 52, and the functions of each piece ofequipment, from the system configuration information 341 b. Theinformation collecting unit 343 also obtains the identifiers ofequipment within the higher-order stack 53 connected to equipment withinthe stack 52, from the connection information 341 a. The informationcollecting unit 343 then obtains the functions of each piece ofequipment within the higher-order stack 53 connected to equipment withinthe stack 52 from the system configuration information 341 b.

The information collecting unit 343 creates the stack operation model321 as connection information, where the connection relation amongequipment of the stack 52 and between equipment of the stack 52 andequipment of the higher-order stack 53 are in a one-on-one relation,based on the obtained information. Creating of the stack operation model321 by the information collecting unit 343 is performed when a failureoccurs (when obtaining at least one of the higher-order stack detectioninformation 71 and own-stack detection information 72), for example.Note that the information collecting unit 343 is not restricted togenerating the stack operation model 321 when trouble occurs, and mayperiodically create the stack operation model 321, such as once a day.Creating the stack operation model 321 periodically enables the neweststack operation model 321 to be constantly available. The informationcollecting unit 343 may also create the stack operation model 321 whenthere is change in the connection information 341 a or the systemconfiguration information 341 b.

Note that FIG. 20 illustrates the stack operation model 321 in theinitial state. In the initial state, the value for failure occurrenceinformation is “0” for each piece of equipment, and the value forfailure effects information is also “0” for each piece of equipment, inthe stack operation model 321.

FIG. 21 is a flowchart illustrating an example of the procedures forinformation collecting processing. The processing illustrated in FIG. 21will be described below following the step numbers.

(Step S221) The information collecting unit 343 reads in the connectioninformation 341 a and system configuration information 341 b from thesystem configuration information storage unit 341.

(Step S222) The information collecting unit 343 generates the stackoperation model 321.

(Step S223) The information collecting unit 343 stores the generatedstack operation model 321 in the stack operation model storage unit 320.

The stack operation model 321 generated in this way is used to performeffect range searching processing by the effects searching unit 344.

FIG. 22 is a diagram illustrating an example of effect range searchingprocessing in downflow processing. The effects searching unit 344searches the range of effects of failure with each of thefailure-affected equipment in the higher-order stack 53 and thefailure-detected equipment in the higher-order stack 53 and stack 52 asstart points. The effects searching unit 344 uses the effect rangesearch route information 311 defined beforehand in searching for therange of effects of failure. The effects searching unit 344 also updatesthe stack operation model 321 in accordance with the results of theeffect range search.

In the example in FIG. 22, the range of effects of failure was searchedwith the failure-affected equipment “app_a” within the stack 53 as astart point, and as a result, equipment “aa”, equipment “bb”, andequipment “cc” within stack 52 have been detected as failure-detectedequipment. Also, the range of effects of failure was searched with thefailure-affected equipment “app_c” within the stack 53 as a start point,and as a result, equipment “dd” and equipment “ee” within stack 52 havebeen detected as failure-detected equipment. Further, the range ofeffects of failure was searched with the failure-affected equipment “bb”within the stack 52 as a start point, and as a result, equipment “aa”and equipment “cc” within stack 52 have been detected asfailure-affected equipment. Note that the failure-affected equipment“app_b” within the stack 53 is not connected to any equipment in thestack 52, so the effects searching unit 344 does not perform a searchfor the range of effects with the failure-affected equipment “app_b” asa start point.

An update state of the stack operation model 321 will be described belowwith reference to FIGS. 23 and 24.

FIG. 23 is a diagram illustrating an example of a stack operation modelin which detection information has been reflected. The effects searchingunit 344 that has obtained the detection information 73 adds informationindicating whether or not the equipment will serve as a start point in asearch (the value of the “start point equipment “column”), to eachrecord within the stack operation model 321. The initial value ofinformation indicating whether or not the equipment will serve as astart point in a search is “0”. The effects searching unit 344 thenreflects information of equipment where a failure has occurred andinformation of equipment that possibly may be affected by failure in thestack operation model 321 indicated in the detection information 73. Theeffects searching unit 344 further sets information indicating thatequipment where a failure has occurred and information of equipment thatpossibly may be affected by failure is equipment that serves as a startpoint for a search, in the stack operation model 321.

In the example in FIG. 23, the value of information indicating whetheror not there has been occurrence of failure is changed to “1” for therecord of equipment “bb”, and the value if information indicatingwhether or not to be start point equipment for a search is changed to“1”. The value of information indicating whether or not there areeffects of failure is changed to “1” for the record of equipment“app_a”, and the value of information indicating whether or not theequipment will be a start point for a search is changed to “1”. Thevalue of information indicating whether or not there has been occurrenceof failure is changed to “1” for the record of equipment “app_c”, thevalue of information indicating whether or not the equipment will be astart point for a search is changed to “1”.

Thereafter, the range of effects of failure is searched for by theeffects searching unit 344, upon which the stack operation model 321 isupdated in accordance with the search results.

FIG. 24 is a diagram illustrating an example of a stack operation modelin which the search results of the range of effects in downflowprocessing have been reflected. FIG. 24 illustrates the stack operationmodel 321 in which the search results such as illustrated in FIG. 22have been reflected. In the example in FIG. 24, the value of informationindicating whether or not there are effects of failure has been changedto “1” for the records of each of equipment “aa”, “cc”, “dd”, and “ee”.

Next, the procedures of effect range searching processing will bedescribed with reference to a flowchart.

FIG. 25 is a flowchart illustrating an example of procedures for effectrange searching processing in downflow processing. The processingillustrated in FIG. 25 will be described below following the stepnumbers.

(Step S231) The effects searching unit 344 receives the detectioninformation 73 from the detection information obtaining unit 342.

(Step S232) The effects searching unit 344 updates the stack operationmodel 321 based on the received detection information 73. For example,the effects searching unit 344 sets information indicatingfailure-detected equipment and failure-affected equipment to the stackoperation model 321, and sets in the stack operation model 321 that thefailure-detected equipment and failure-affected equipment will be startpoints for an effect range search.

(Step S233) The effects searching unit 344 selects one unselected startpoint device out of the devices regarding which the stack operationmodel 321 indicates as being a start point for a search (start pointequipment).

(Step S234) The effects searching unit 344 decides an effect rangesearch route to apply. For example, in a case where the start pointequipment is equipment within the stack 52, the effects searching unit344 references the failure and search route correlation table 311 a ofthe stack in the effect range search route information 311 (see FIG. 7),and obtains an identifier for the search route corresponding to the setof the type of failure that has occurred and the function of thefailure-detected equipment. The effects searching unit 344 thenreferences the search route information 311 c and identifies the searchroute corresponding to the obtained identifier to be the effect rangesearch route to apply.

In a case where the start point equipment is equipment within thehigher-order stack 53, the effects searching unit 344 references thefailure and search route correlation table 311 b of the stack in theeffect range search route information 311 (see FIG. 7), and obtains anidentifier for the search route corresponding to the set of the type offailure that has occurred and the function of the failure-detectedequipment. The effects searching unit 344 then references the searchroute information 311 c and identifies the search route corresponding tothe obtained identifier to be the effect range search route to apply.

(Step S235) The effects searching unit 344 searches for equipment withinthe range of effects, based on the effect range search route to apply.For example, the effects searching unit 344 starts searching from thestart point equipment, and searches adjacent equipment of the functionindicated in the effect range search route, in the order indicated bythe effect range search route. The effects searching unit 344 judgesequipment reached by the search to be equipment within the range ofeffects.

(Step S236) The effects searching unit 344 changes the value to “1” forinformation indicating whether or not there are effects of the failure,for equipment within the range of effects in the stack operation model321.

(Step S237) The effects searching unit 344 judges whether or not allstart point equipment has been selected. In a case where all start pointequipment has been selected, the effects searching unit 344 ends theeffect range searching processing. If there is unselected start pointequipment, the effects searching unit 344 advances the flow to stepS233.

Thus, failure effect range searching processing within the stack 52 isperformed, and the stack operation model 321 is updated in accordancewith the results of processing. Thereafter, search results notificationprocessing is performed by the search results notifying unit 345.

FIG. 26 is a diagram illustrating an example of search resultsnotification processing in downflow processing. The search resultsnotifying unit 345 references the stack operation model 321, andgenerates post-own-stack-search detection information 74 indicatingfailure-detected equipment and failure-affected equipment in the stack52. The search results notifying unit 345 then transmits the generatedpost-own-stack-search detection information 74 to the effect rangeidentifying device 400 of the lower-order stack 51.

The search results notifying unit 345 also references the stackoperation model 321 and generates display data 81 indicating thefailure-detected equipment and failure-affected equipment at thehigher-order stack 53 and the stack 52 to which it belongs,respectively. The search results notifying unit 345 then transmits thedisplay data 81 to the terminal device 30 that the administrator of thestack 52 uses. Thus, an image corresponding to the display data 81 isdisplayed on the terminal device 30.

The display data 81 indicates the connection relation among equipmentwithin the stack 52, and the connection relation between equipment inthe stack 52 and equipment in the higher-order stack 53, for example.The display data 81 indicates the failure-detected equipment andfailure-affected equipment in a highlighted display. For example,settings are made in the display data 81 so that the failure-detectedequipment and failure-affected equipment are displayed in differentcolors.

FIG. 27 is a flowchart illustrating an example of procedures of searchresults notification processing to a lower-order stack. The processingillustrated in FIG. 27 will be described following the step numbers.

(Step S241) The search results notifying unit 345 reads in the stackoperation model 321 from the stack operation model storage unit 320.

(Step S242) The search results notifying unit 345 transmits the displaydata 81 to the terminal device 30, so that the range of effects offailure at the stack 52 is displayed on the terminal device 30.

(Step S243) The search results notifying unit 345 transmits thepost-own-stack-search detection information 74 indicating the searchresults of the range of effects at the stack 52, to the lower-orderstack 51. Note that in a case where the stack 52 is the lowest-layerstack, transmission of the post-own-stack-search detection information74 to the lower-order stack 51 is not performed.

Downflow processing is performed in this way. The post-own-stack-searchdetection information 74 transmitted in the downflow processing at thestack 52 is received by the effect range identifying device 400 of thelower-order stack 51. Downflow processing is then performed in the sameway at the effect range identifying device 400. The downflow processingat the effect range identifying device 400 detects devices in the stack51 that are in the range of effects of failure.

FIG. 28 is a diagram illustrating an example of the range of effects offailure at the lowest-layer stack. Effect range searching processingwith equipment “cc” as the start point is executed at the effect rangeidentifying device 400 of the stack 51, and equipment “xxx” is detectedas failure-affected equipment, as illustrated in FIG. 28. Effect rangesearching processing with equipment “ee” as the start point is alsoexecuted, and equipment “yyy” is detected as failure-affected equipment.

After the downflow processing, the effect range identifying devices 200,300, and 400 of the respective stacks execute upflow processing at apredetermined timing. The effect range identifying device 400 within thelowest-layer stack 51 starts the upflow processing when the downflowprocessing ends. The effect range identifying devices 200 and 300 of thestacks 52 and 53 other than the lowest-layer stack execute upflowprocessing upon receiving information indicating the search results ofthe range of effects at the lower-order stack. For example, at the stack52, the upflow processing unit 350 performs upflow processing.

FIG. 29 is a diagram illustrating an example of functions of an upflowprocessing unit. The upflow processing unit 350 has a detectioninformation obtaining unit 351, an effects searching unit 352, and asearch results notifying unit 353.

The detection information obtaining unit 351 obtains informationindicating failure-detected equipment and failure-affected equipment(lower-order stack detection information) from the effect rangeidentifying device 400 of the lower-order stack 51. The effectssearching unit 352 searches the range of effects of failure with thefailure-detected equipment and failure-affected equipment indicated bythe lower-order stack detection information as start points. The searchresults notifying unit 353 transmits information of the failure-detectedequipment and failure-affected equipment detected at the stack 52, tothe effect range identifying device 200 of the higher-order stack 53.The search results notifying unit 353 also notifies the terminal device30 that the administrator of the stack 52 uses of the range of effectsof failure.

Upon the upflow processing unit 350 receiving identifiers of thefailure-detected equipment and failure-affected equipment regarding thefailure that has occurred (lower-order stack detection information) fromthe effect range identifying device 400 of the lower-order stack 51,upflow processing is started.

FIG. 30 is a diagram illustrating an example of procedures for upflowprocessing. The processing illustrated in FIG. 30 will be describedbelow following the step numbers.

(Step S301) The detection information obtaining unit 351 performsprocessing of obtaining lower-order stack detection information. Detailsof the processing of obtaining detection information from thelower-order stack 51 will be described later (see FIG. 32).

(Step S302) The effects searching unit 352 performs effect rangesearching processing in the upflow. Details of effect range searchingprocessing in the upflow will be described later (see FIG. 36).

(Step S303) The search results notifying unit 353 performs searchresults notification processing to the higher-order stack 53. Details ofsearch results notification processing to the higher-order stack 53 willbe described later (see FIG. 38).

When obtaining lower-order stack detection information, upflowprocessing is performed by these procedures.

FIG. 31 is a diagram illustrating an example of the processing forobtaining lower-order stack detection information. In a case wherefailure-affected equipment such as illustrated in FIG. 28 is detected atthe lower-order stack 51, the effect range identifying device 400generates lower-order stack detection information 75 indicatingequipment in the stack 52 connected to failure-affected equipment in thestack 51. The generated lower-order stack detection information 75 istransmitted from the effect range identifying device 400 to the effectrange identifying device 300, whereupon the detection informationobtaining unit 351 executes the processing for obtaining lower-orderstack detection information.

FIG. 32 is a flowchart illustrating an example of procedures forprocessing for obtaining lower-order stack detection information. Theprocessing illustrated in FIG. 32 will be described below following thestep numbers.

(Step S311) The detection information obtaining unit 351 obtains thelower-order stack detection information 75 indicating equipment withinthe higher-order stack 52 dependent on the failure-affected equipmentwithin the stack 51, from the effect range identifying device 400.

(Step S312) The detection information obtaining unit 351 transmits theobtained lower-order stack detection information 75 to the effectssearching unit 352.

The effects searching unit 352 that has received the lower-order stackdetection information 75 performs effect range searching processing.

FIG. 33 is a diagram illustrating an example of effect range searchingprocessing in the upflow. The effects searching unit 352 searches forthe range of effects of failure of equipment in the stack 52 connectedto the failure-affected equipment in the lower-order stack 51 as thestart point, based on the lower-order stack detection information 75.The effects searching unit 352 uses the effect range search routeinformation 311 defined beforehand in the searching for the range ofeffects of failure. The effects searching unit 352 also updates thestack operation model 321 in accordance with the results of effect rangesearching.

In the example in FIG. 33, equipment “aa” and equipment “bb” in thestack 52 have been detected as being failure-affected equipment as aresult of searching for the range of effects of failure with theequipment “cc” in the stack 52 as the start point. Also, equipment “dd”in the stack 52 has been detected as being failure-affected equipment asa result of searching for the range of effects of failure with theequipment “ee” in the stack 52 as the start point. Further, equipment“gg” in the stack 52 has been detected as being failure-affectedequipment as a result of searching for the range of effects of failurewith the equipment “ff” in the stack 52 as the start point.

The update state of the stack operation model 321 will be describedbelow with reference to FIGS. 34 and 35.

FIG. 34 is a diagram illustrating an example of a stack operation modelin which is reflected lower-order stack detection information. Theeffects searching unit 352 that has obtained the lower-order stackdetection information 75 initializes the column of start point equipmentin the stack operation model 321. The effects searching unit 352 setsinformation, indicating that the equipment in the stack 52 connected tothe failure-affected equipment in the lower-order stack 51 is equipmentto serve as a start point of a search, indicated in the lower-orderstack detection information 75, to the stack operation model 321. In theexample in FIG. 34, information indicating whether or not a device toserve as a start point of a search is changed to “1” for each ofequipment “cc”, “ee”, and “ff”.

Thereafter, the effects searching unit 352 searches the range of effectsof failure, whereupon the stack operation model 321 is updated inaccordance with the search results.

FIG. 35 is a diagram illustrating an example of a stack operation modelin which is reflected the search results of the range of effects inupflow processing. The stack operation model 321 reflecting the searchresults illustrated in FIG. 33 is illustrated in FIG. 35. In the examplein FIG. 35, the value of information indicating whether or not there areeffects of the failure is changed to “1” for the records of eachequipment “ff” and “gg”.

Next, the procedures of effect range searching processing will bedescribed with reference to a flowchart.

FIG. 36 is a flowchart illustrating an example of procedures for effectrange searching processing in upflow processing. The processingillustrated in FIG. 36 will be described below following the stepnumbers.

(Step S321) The effects searching unit 352 receives the lower-orderstack detection information 75 from the detection information obtainingunit 351.

(Step S322) The effects searching unit 352 resets the value for startpoint equipment to “0” for all records of the stack operation model 321.

(Step S323) The effects searching unit 352 updates the stack operationmodel 321 based on the received lower-order stack detection information75. For example, the effects searching unit 352 makes settings to thestack operation model 321 to the effect that equipment connected to thefailure-affected equipment in the lower-order stack 51 will serve asstart point equipment for effect range searching, as illustrated in FIG.34.

(Step S324) The effects searching unit 352 selects one of the unselectedstart point equipment out of the equipment indicated in the stackoperation model 321 to be a start point for searching (start pointequipment).

(Step S325) The effects searching unit 352 decides an effect rangesearch route to apply. For example, the effects searching unit 352references the failure and search route correlation table 311 a of thestack in the effect range search route information 311 (see FIG. 7), andobtains an identifier for the search route corresponding to the set ofthe type of failure that has occurred and the function of thefailure-detected equipment. The effects searching unit 352 thenreferences the search route information 311 c and identifies the searchroute corresponding to the obtained identifier to be the effect rangesearch route to apply.

(Step S326) The effects searching unit 352 searches for equipment withinthe range of effects, based on the effect range search route to apply.For example, the effects searching unit 352 starts searching from thestart point equipment, and searches adjacent equipment of the functionindicated in the effect range search route, in the order indicated bythe effect range search route. The effects searching unit 352 judgesequipment reached by the search to be equipment within the range ofeffects.

(Step S327) The effects searching unit 352 changes the value to “1” forinformation indicating whether or not there are effects of the failure,for equipment within the range of effects in the stack operation model321.

(Step S328) The effects searching unit 352 judges whether or not allstart point equipment has been selected. In a case where all start pointequipment has been selected, the effects searching unit 352 ends theeffect range searching processing. If there is unselected start pointequipment, the effects searching unit 352 advances the flow to stepS324.

Thus, failure effect range searching processing within the stack 52 isperformed, and the stack operation model 321 is updated in accordancewith the results of processing. Thereafter, search results notificationprocessing is performed by the search results notifying unit 353.

FIG. 37 is a diagram illustrating an example of search resultsnotification processing in upflow processing. The search resultsnotifying unit 353 references the stack operation model 321, andgenerates post-own-stack-search detection information 76 indicatingequipment in the higher-order stack 53 connected to any of thefailure-detected equipment and failure-affected equipment in the stack52. The search results notifying unit 353 then transmits the generatedpost-own-stack-search detection information 76 to the effect rangeidentifying device 200 of the higher-order stack 53.

The search results notifying unit 353 also references the stackoperation model 321 and generates display data 82 indicating thefailure-detected equipment and failure-affected equipment at thehigher-order stack 53 and the stack 52 to which it belongs,respectively. The search results notifying unit 353 then transmits thedisplay data 82 to the terminal device 30 that the administrator of thestack 52 uses. Thus, an image corresponding to the display data 82 isdisplayed on the terminal device 30.

FIG. 38 is a flowchart illustrating an example of procedures of searchresults notification processing to a higher-order stack. The processingillustrated in FIG. 38 will be described below following the stepnumbers.

(Step S331) The search results notifying unit 353 reads in the stackoperation model 321 from the stack operation model storage unit 320.

(Step S332) The search results notifying unit 353 transmits the displaydata 82 to the terminal device 30, so that the range of effects offailure at the stack 52 is displayed on the terminal device 30.

(Step S333) The search results notifying unit 353 transmits thepost-own-stack-search detection information 76 indicating the equipmentof the higher-order stack 53 connected to the equipment in the stack 52included in the range of effects (failure-detected equipment andfailure-affected equipment), to the higher-order stack 53.

Upflow processing is performed in this way. Consequently, the range ofeffects of failure of equipment in the stack 52 is correctly displayedon the terminal device 30.

FIG. 39 is a diagram illustrating an example of a failure effect rangedisplay screen 83. The failure effect range display screen 83 isdisplayed at the terminal device 30, based on display data 81 and 82transmitted from the effect range identifying device 300. In the examplein FIG. 39, the display data 81 transmitted at the time of performingdownflow processing is displayed as results of reflecting effects, fromthe higher-order stack 53. The display data 82 transmitted at the timeof performing upflow processing also is displayed as results ofreflecting effects, from the higher-order and lower-order stacks.

The administrator of the stack 52 may appropriately judge the range ofeffects of failure by referencing the failure effect range displayscreen 83. That is to say, the administrator may appropriately recognizenot only propagation of effects of the failure within the stack 52, butalso effects of the failure via the higher-order stack 53 or lower-orderstack 51. As a result, when handling the failure, the administrator mayminimize deterioration in quality of service due to the failure that hasoccurred, by handling, with priority, equipment that has a possibilityof being affected by the failure.

Although display data has been described in the second embodiment asbeing output to the terminal device 30 in both downflow processing andupflow processing, output of display data in the downflow processing maybe omitted, for example.

Third Embodiment

Next, a third embodiment will be described. The third embodimentinvolves overlaying search results of the range of effects of failure,thereby enabling distinguishing of the difference in the extent ofeffects of the failure that failure-affected equipment will receive.

For example, in the second embodiment, the effect range identifyingdevice 300 of the stack 52 performs a search of the range of effects offailure with multiple pieces of equipment as start points in downflowprocessing and upflow processing. Thus, there will be equipmentdetermined to be in the range of effects of failure from multipledifferent start points. The greater the number of times of having beendetermined to be in the range of effects in the effect range search, thegreater the probability of being affected by the failure may beconceived to be. Accordingly, in the third embodiment, the number oftimes of having been determined to be in the range of effects is countedfor each piece of equipment at each of the effect range identifyingdevices 200, 300, and 400, and the counted value is displayed as theseverity for each piece of equipment. Accordingly, the administrator maycomprehend the difference in the probability that each of the multiplepieces of failure-affected equipment will be affected by the failure.Consequently, a situation where the administrator starts researching andhandling from equipment that is not important, while leaving the mostimportant equipment unattended to, may be suppressed.

Points of difference between the third embodiment and the secondembodiment will be described below.

A severity column is provided to the stack operation model in the thirdembodiment instead of the effects of failure column, and the number oftimes of having been determined to be in the range of effects of failureis set in the severity column.

FIG. 40 is a diagram illustrating an example of effect range searchingprocessing in downflow processing according to the third embodiment. Inthe example in FIG. 40, the equipment “aa” and “cc” in the stack 52 arewithin the range of effects when the equipment ““app_a” in the stack 53is the start point, and also are in the range of effects when theequipment “bb” in the stack 52 is the start point. As a result, theseverity for the equipment “aa” and “cc” is “2”. On the other hand, theequipment “dd” and “cc” in the stack 52 are within the range of effectswhen the equipment ““app_c” in the stack 53 is the start point, so theseverity for the equipment “dd” and “cc” is “1”.

FIG. 41 is a diagram illustrating an example of a stack operation modelin which has been reflected the search results for the range of effectsin the downflow processing according to the third embodiment. Whenupdating a stack operation model 322 in accordance with the searchresults for the range of effects, the effects searching unit 344 setsthe number of times that each piece of equipment has been detected asbeing within the range of effects (severity) as the value in the columnof severity for the record corresponding to that equipment. In theexample in FIG. 40, the value in the column for severity is “2” for therecords of the equipment “aa” and “cc” in the stack operation model 322.The value in the column for severity is “1” for the records of theequipment “dd” and “cc” in the stack operation model 322.

Next, the procedures for effect range search processing in the downflowprocessing will be described.

FIG. 42 is a flowchart illustrating an example of procedures fordownflow processing according to the third embodiment. Of the processesin FIG. 42, steps S401 through S405 and S407 are each the same as thesteps S231 through S235 and S237 of the processes in the secondembodiment illustrated in FIG. 25. Accordingly, the processing of stepS406 that differs from the second embodiment will be described below.

(Step S406) The effects searching unit 344 increments by “1” the valuein the column for severity of the record of equipment within the rangeof effects in the stack operation model 322.

Thus, each time equipment is detected as being in the range of effectsin the effect range searching processing, the value in the column forseverity is incremented by 1, so the number of times of each piece ofequipment having been detected as being in the range of effects offailure may be counted. The search results notifying unit 345 thentransmits information including the number of times of being within therange of effects as severity, to the effect range identifying device 400of the lower-order stack 51 and the terminal device 30.

FIG. 43 is a diagram illustrating an example of search resultsnotification processing in the downflow processing according to thethird embodiment. The search results notifying unit 345 references thestack operation model 322, and generates post-own-stack-search detectioninformation 74 a indicating failure-detected equipment andfailure-affected equipment in the stack 52. The post-own-stack-searchdetection information 74 a indicates the severity of the failureregarding failure-affected equipment. The search results notifying unit345 then transmits the generated post-own-stack-search detectioninformation 74 a to the effect range identifying device 400 of thelower-order stack 51.

The search results notifying unit 345 also references the stackoperation model 322 and generates display data 81 a indicating thefailure-detected equipment and failure-affected equipment at thehigher-order stack 53 and the stack 52 to which it belongs,respectively. The display data 81 a has the display form forfailure-affected equipment set to a display form corresponding to theseverity. For example, the color of an object indicatingfailure-affected equipment is set to a different color for eachseverity.

The search results notifying unit 345 then transmits the display data 81a to the terminal device 30 that the administrator of the stack 52 uses.Thus, an image corresponding to the display data 81 a is displayed onthe terminal device 30.

This so far is the downflow processing according to the thirdembodiment. The severity is also updated in upflow processing as well.The processing of obtaining lower-order stack detection information inthe upflow processing according to the third embodiment is the same asin the second embodiment. Accordingly, the lower-order stack detectioninformation 75 illustrated in FIG. 31 is transmitted to the effectssearching unit 352. The effects searching unit 352 then performs effectrange searching processing in the upflow processing, with equipmentindicated by the lower-order stack detection information 75 as startpoints.

FIG. 44 is a diagram illustrating an example of effect range searchingprocessing in the upflow according to the third embodiment. The effectssearching unit 352 increments the value of severity within the stackoperation model 322 regarding equipment within the range of effectsdetected by the effect range searching processing, as illustrated inFIG. 44.

The update state of the stack operation model 322 will be describedbelow with reference to frigs. 45 and 46.

FIG. 45 is a diagram illustrating an example of a stack operation modelin which is reflected lower-order stack detection information accordingto the third embodiment. The effects searching unit 352 that hasobtained the lower-order stack detection information 75 initializes thecolumn of start point equipment in the stack operation model 322. Theeffects searching unit 352 sets information, indicating that theequipment in the stack 52 connected to the failure-affected equipment inthe lower-order stack 51 is equipment to serve as a start point of asearch, indicated in the lower-order stack detection information 75, tothe stack operation model 322.

Thereafter, the effects searching unit 352 searches the range of effectsof failure, whereupon the stack operation model 322 is updated inaccordance with the search results.

FIG. 46 is a diagram illustrating an example of a stack operation modelin which is reflected the search results of the range of effects inupflow processing according to the third embodiment. The stack operationmodel 322 reflecting the search results illustrated in FIG. 44 isillustrated in FIG. 46. The value of severity is incremented by “1” forthe records of each of equipment “aa”, “cc”, “dd”, “ee”, “ff”, and “gg”in the stack operation model 322.

Next, the procedures of effect range searching processing will bedescribed with reference to a flowchart.

FIG. 47 is a flowchart illustrating an example of the procedures ofeffect range searching processing in the upflow processing according tothe third embodiment. Of the processing illustrated in FIG. 47, theprocesses of steps S411 through S416 and S418 are each the same as stepsS321 through S326 and S328 of the processing according to the secondembodiment illustrated in FIG. 36. The processing of step S417 thatdiffers from the second embodiment will be described below.

(Step S417) The effects searching unit 352 increments the value in thecolumn of severity by “1” for the records corresponding to equipment inthe range of effects in the stack operation model 322.

Accordingly, each time of being detected within the range of effects byeffect range searching in the upflow processing, the severity of eachpiece of equipment counted in the downflow processing is incrementedby 1. The search results notifying unit 353 transmits informationincluding the number of times of being within the range of effects asseverity to the effect range identifying device 200 of the higher-orderstack 53 and the terminal device 30.

FIG. 48 is a diagram illustrating an example of search resultsnotification processing in upflow processing according to the thirdembodiment. The search results notifying unit 353 references the stackoperation model 322, and generates post-own-stack-search detectioninformation 76 indicating equipment in the higher-order stack 53connected to any of the failure-detected equipment and failure-affectedequipment in the stack 52. The search results notifying unit 353 thentransmits the generated post-own-stack-search detection information 76to the effect range identifying device 200 of the higher-order stack 53.

The search results notifying unit 353 also references the stackoperation model 322 and generates display data 82 a indicating thefailure-detected equipment and failure-affected equipment at thehigher-order stack 53 and the stack 52 to which it belongs,respectively. The display data 82 a has the display form forfailure-affected equipment set to a display form corresponding to theseverity. For example, the color of an object indicatingfailure-affected equipment is set to a different color for eachseverity.

The search results notifying unit 353 then transmits the display data 82a to the terminal device 30 that the administrator of the stack 52 uses.Thus, an image corresponding to the display data 82 a is displayed onthe terminal device 30.

In this way, in the third embodiment the severity of failure-affectedequipment is obtained, and difference in severity is displayed.Accordingly, the administrator may handle, with priority, equipment thathas a high probability of being affected by the failure, and mayaccurately and speedily handle the failure.

Fourth Embodiment

Next, a fourth embodiment will be described. In the fourth embodiment,the seriousness of a failure occurring at equipment providing a serviceis obtained in accordance with the usage state of that service, for eachstack, and information regarding seriousness is exchanged among theeffect range identifying devices 200, 300, and 400 of the respectivestacks. Knowing the seriousness when a failure occurs in equipment atanother stack enables handling failure-affected equipment of the ownstack to be handled in an appropriate order.

In a case where the stacks are being managed by different corporations,for example, the corporations managing the stacks are not able todisclose information of customers using the services. Accordingly, in acase where equipment at a lower-order stack is affected by a failure,the administrator of the lower-order stack is not able to tell howimportant the service provided by equipment at the higher-order stackusing that equipment is. There are various aspects to importance ofequipment, such as for example, the number of units of equipmentconnected to that equipment, usage purpose such as developmentalenvironment or implementation environment, the number of customers usingthe equipment, contractual importance of using the equipment, socialimportance such as bank-related, and so on. Such information serving asa standard for judging importance of equipment within a certain stack isclosely related to customer information, and may not be informed to anadministrator of another stack.

Accordingly, in the fourth embodiment, the importance in a case whereequipment in a certain stack is affected by a failure is replaced by anumerical value of seriousness, and transmitted to the effect rangeidentifying devices of the other stacks. The effect range identifyingdevices that have received the seriousness of equipment within anotherstack judge the seriousness regarding equipment within their own stacks,taking into consideration the seriousness regarding equipment in ahigher-order stack. This allows the seriousness of equipment within ownstacks to be accurately calculated at each stack, and the administratorsmay handle appropriately so that effects of the failure do not lead toserious deterioration in service quality.

Points of difference between the fourth embodiment and the thirdembodiment will be described below.

FIG. 49 is a diagram illustrating handover of information includingseriousness. For example, the effect range identifying device 300obtains information, where the identifier of a piece of failure-affectedequipment has added thereto the seriousness of that failure-affectedequipment, from the effect range identifying device 200 in thehigher-order stack 53 using equipment in the own stack. The effect rangeidentifying device 300 then provides the information of the stack 52(the identifier of the failure-affected equipment with the seriousnessadded thereto) and information obtained from the higher-order stack 53,to the effect range identifying device 400 of the lower-order stack 51.

The effect range identifying device 400 of the lower-order stack 51searches for failure-affected equipment based on the obtainedinformation, and transmits identifiers of new failure-affected equipmentwithin the stack 52 connected to the failure-affected equipment in thestack 52 to the effect range identifying device 300 of the stack 52. Theeffect range identifying device 300 searches for failure-affectedequipment based on the obtained information, and transmits identifiersof new failure-affected equipment within the higher-order stack 53connected to the failure-affected equipment in the stack 52, to theeffect range identifying device 200 of the stack 53.

Thus, in the fourth embodiment, the seriousness is calculated at thetime of downflow processing, to calculate seriousness within the effectrange identifying device 300.

FIG. 50 is a diagram illustrating the functions of a downflow processingunit according to the fourth embodiment. A downflow processing unit 340a according to the fourth embodiment has, in addition to the componentsthat the downflow processing unit 340 according to the second embodimentillustrated in FIG. 15 has, a seriousness calculating unit 346.

The seriousness calculating unit 346 calculates the seriousness of eachof failure-detected equipment and failure-affected equipment, based onthe usage states of services provided at each of the failure-detectedequipment and failure-affected equipment in the stack 52. Forfailure-detected equipment or failure-affected equipment connected tothe higher-order stack 53, the seriousness calculating unit 346 uses asummed value of the calculated seriousness and the seriousness ofequipment in the higher-order stack 53 connected to, as the seriousnessof the failure-detected equipment or failure-affected equipment. Theseriousness calculating unit 346 then sets the calculated seriousness inthe stack operation model.

Note that the following method is conceivable as a method to calculateseriousness.

Method of Calculating Seriousness Based on Contractual Usage Fees

For example, a database is provided in the effect range identifyingdevice 300 that stores monthly usage fees of customers using servicesprovided at the stack 52. The seriousness calculating unit 346 evaluatesthe usage fees of the previous month on a scale of 1 to 5, and sets theseriousness higher for customers paying greater usage fees. For example,the seriousness calculating unit 346 sets the seriousness for equipmentused by customers of which the usage fees are evaluated to be highest,to “100”. The seriousness calculating unit 346 sets the seriousness forequipment used by customers of which the usage fees are evaluated to besecond highest, to “80”. Thereafter, the seriousness calculating unit346 lowers the value for seriousness by 20, for each level theevaluation is lowered to.

Method of Calculating Seriousness Based on Damages Occurring in PastFailures

For example, a database is provided in the effect range identifyingdevice 300 that stores business types, customer size, and damagesthereof, with regard to past cases of failures, and a database storingcurrent customer businesses and customer size. The seriousnesscalculating unit 346 then estimates, from business types, customer size,and damages thereof, with regard to past cases of failures, that similardamages will be incurred if services are stopped regarding customers ofthe same business type and customer size, and calculates the seriousnessin accordance with estimated damages. For example, the larger the scaleof damages is, the larger the seriousness calculating unit 346 sets thevalue of seriousness.

Method of Calculating Seriousness Based on Difference of WhetherDevelopment Environment or Operational Environment

For example, a database is provided in the effect range identifyingdevice 300 that stores whether usage of equipment by customers is usageas a development environment or usage as an operational environment. Theseriousness calculating unit 346 then calculates the seriousness of theequipment in accordance with whether the equipment is being used as adevelopment environment, or an operational environment where theequipment is actually used by the customer for business. The seriousnesscalculating unit 346 sets the seriousness of the equipment being used inan operational environment higher than the seriousness of the equipmentbeing used in development environment, for example.

Method of Calculating Seriousness Based on Number of Units Connected atHigher-Order Stack

For example, the seriousness calculating unit 346 calculates the numberof units within the higher-order stack 53 that are connected to theequipment in the stack 52. The seriousness calculating unit 346 thencalculates the seriousness in accordance with the number of units withinthe higher-order stack 53 that are connected to each piece of equipment.For example, the seriousness calculating unit 346 evaluates the numberof units within the higher-order stack 53 connected to each piece ofequipment on a scale of 1 to 5, with the seriousness of the equipmenthaving a greater number of connections being higher in value.

Method of Calculating Seriousness Based on Type of Business of CustomersUsing Equipment

For example, a database is provided in the effect range identifyingdevice 300 that stores business types of customers. The seriousnesscalculating unit 346 sets equipment used by customers of business typeswith high social importance, such as banks and so forth, so as to behigher than other equipment.

The seriousness calculating unit 346 may calculate seriousness by one ofthe above-described methods, or take a sum of seriousness calculated bymultiple methods as the seriousness of the equipment.

FIG. 51 is a diagram illustrating an example of a stack operation modelaccording to the fourth embodiment. A stack operation model 323according to the fourth embodiment has a column for seriousness added tothe records of the equipment. The initial value of seriousness is “0”,and when corresponding equipment becomes failure-detected equipment orfailure-affected equipment, a value indicating the seriousness of thatequipment is set to the column for seriousness.

FIG. 52 is a diagram illustrating an example of the procedures fordownflow processing in the fourth embodiment. The processing illustratedin FIG. 52 will be described below following the step numbers.

(Step S501) The detection information obtaining unit 342 performsdetection information obtaining processing. The details of detectioninformation obtaining processing are almost the same as the detectioninformation obtaining processing according to the second embodimentillustrated in FIG. 19. The detection information obtaining processingaccording to the fourth embodiment differs from the second embodimentwith regard to the point that the information to be obtained includesthe value of seriousness for failure-detected equipment orfailure-affected equipment.

(Step S502) The information collecting unit 343 performs informationcollection processing. A stack operation model is created by theinformation collection processing. Details of the information collectionprocessing are almost the same as the information collection processingin the second embodiment illustrated in FIG. 21. The difference betweenthe information collection processing according to the fourth embodimentand the second embodiment is the point that a column is included in thestack operation model 323 being generated, to set the seriousness ofeach piece of equipment, as illustrated in FIG. 51.

(Step S503) The effects searching unit 344 performs effect rangesearching processing. Details of the effect range searching processingis almost the same as the effect range searching processing according tothe third embodiment illustrated in FIG. 42. The effect range searchingprocessing according to the fourth embodiment differs from the thirdembodiment with regard to the point that when updating the stackoperation model 323 in accordance with detection information obtainedfrom the information collecting unit 343, the value for seriousness isalso updated.

(Step S504) The seriousness calculating unit 346 performs seriousnesscalculation processing. Details of the seriousness calculationprocessing will be described later (see FIG. 57).

(Step S505) The search results notifying unit 345 performs searchresults notification processing to the lower-order stack 51. Details ofthe search results notification processing to the lower-order stack 51are almost the same as the search results notification processing to thelower-order stack 51 according to the second embodiment illustrated inFIG. 27. The search results notification processing to the lower-orderstack 51 according to the fourth embodiment differs from the secondembodiment with regard to the point that information of seriousness foreach piece of equipment is included in the information regarding whichnotification is made.

The processing of the steps in FIG. 52 will be described below indetail.

FIG. 53 is a diagram illustrating an example of detection informationobtaining processing according to the fourth embodiment. The detectioninformation obtaining unit 342 obtains higher-order stack detectioninformation 71 b and own-stack detection information 72 b, asillustrated in FIG. 53.

The higher-order stack detection information 71 b has set therein, incorrelation with identifiers of equipment (equipment names) within thehigher-order stack 53, the stack No. of the stack to which the equipmentbelongs, seriousness, information indicating whether or not there hasbeen occurrence of failure, and the number of times of being detected asbeing in the range of effects of failure (severity). In the example inFIG. 53, the seriousness of equipment “app_a” is “100”, the seriousnessof equipment “app_b” is “10”, and the seriousness of equipment “app_c”is “80”.

The own-stack detection information 72 b has set therein, in correlationwith identifiers of equipment (equipment names) within the stack 52 towhich the effect range identifying device 300 belongs, the stack No. ofthe stack to which the equipment belongs, seriousness, information ofoccurrence of failure, and severity. In the example in FIG. 53, theseriousness of equipment “bb” is “0”.

The detection information obtaining unit 342 generates detectioninformation 73 b where the higher-order stack detection information 71 band own-stack detection information 72 b have been integrated, andtransmits the generated detection information 73 b to the effectssearching unit 344. The effects searching unit 344 updates the stackoperation model 323 based on the received detection information 73 b.

FIG. 54 is a diagram illustrating an example of a stack operation modelin which the detection information according to the fourth embodimenthas been reflected. The effects searching unit 344 that has obtained thedetection information 73 b adds information indicating whether or notequipment to serve as a start point for searching (the value of the“start point equipment” column) in each record in the stack operationmodel 323. The effects searching unit 344 reflects, in the stackoperation model 323, information of equipment where a failure hasoccurred, and information the severity of equipment where there is apossibility of being affected by a failure, illustrated in the detectioninformation 73 b. The effects searching unit 344 also sets informationto the effect that equipment where a failure has occurred and equipmentof which there is a possibility of being affected by a failure, isequipment to be a start point of a search, in the stack operation model323. The effects searching unit 344 further sets the seriousness ofequipment indicated in the detection information 73 b as the seriousnessof the relevant equipment in the stack operation model 323.

Thereafter, upon the range of effects of failure being searched by theeffects searching unit 344, the stack operation model 323 is updated inaccordance with the search results.

FIG. 55 is a diagram illustrating an example of a stack operation modelin which are reflected the search results of the range of effects in thedownflow processing according to the fourth embodiment. FIG. 55illustrates the stack operation model 323 where the search results suchas illustrated in FIG. 40 have been reflected. In the example in FIG.55, the value of severity has been changed to “2” for the records forequipment “aa” and “cc”, and value of severity has been changed to “1”for the records for equipment “dd” and “ee”.

Upon the effect range searching processing in the downflow processingending, the seriousness of the failure-affected equipment is calculatedby the seriousness calculating unit 346, and the calculated seriousnessis set in the stack operation model 323.

FIG. 56 is a diagram illustrating an example of setting seriousness in astack operation model. The seriousness calculating unit 346 firstcalculates the seriousness of the failure-detected equipment andfailure-affected equipment in the stack 52 without taking intoconsideration the seriousness of equipment in the higher-order stack 53.In the example in FIG. 56, the seriousness of equipment “aa” is “50”,the seriousness of equipment “bb” is “80”, the seriousness of equipment“cc” is “30”, the seriousness of equipment “dd” is “30”, and theseriousness of equipment “ee” is “60”.

For equipment connected to failure-detected equipment orfailure-affected equipment in the higher-order stack 53, the seriousnesscalculating unit 346 adds the seriousness of the equipment of theconnected higher-order stack 53 to the seriousness of the equipmentitself. In the example in FIG. 56, the seriousness “100” of theequipment “app_a” is added to the own seriousness of the equipment “aa”that is “50”, so the seriousness of the equipment “aa” is “150”. Also,the seriousness “80” of the equipment “app_c” is added to the ownseriousness of the equipment “dd” that is “30”, so the seriousness ofthe equipment “dd” is “110”.

The seriousness calculating unit 346 sets the value of seriousnesscalculated for the equipment within the stack 52 to the column forseriousness of the records of the relevant equipment in the stackoperation model 323.

The following is a description of procedures for seriousness calculationprocessing with reference to a flowchart.

FIG. 57 is a flowchart illustrating an example of procedures forseriousness calculation processing. The processing illustrated in FIG.57 will be described below following the step numbers.

(Step S511) The seriousness calculating unit 346 reads in the stackoperation model 323 from the stack operation model storage unit 320.

(Step S512) The seriousness calculating unit 346 calculates theseriousness of failure-detected equipment and failure-affected equipmentin the stack 52. The seriousness calculating unit 346 does not take intoconsideration the seriousness of equipment in the higher-order stack 53in this step.

(Step S513) The seriousness calculating unit 346 adds, to theseriousness of the equipment in the stack 52, the seriousness of theequipment in the higher-order stack 53 connected to that equipment.

(Step S514) The seriousness calculating unit 346 updates the seriousnessof each piece of equipment in the stack operation model 323 to the valueof the calculated seriousness.

Thus, searching processing of the range of effects of failure in thestack 52 is performed, and the seriousness of the stack operation model323 is updated in accordance with the results of processing. Thereafter,search results notification processing is performed by the searchresults notifying unit 345.

FIG. 58 is a diagram illustrating an example of search resultsnotification processing in the downflow processing according to thefourth embodiment. The search results notifying unit 345 references thestack operation model 323 and generates post-own-stack-search detectioninformation 74 b indicating failure-detected equipment andfailure-affected equipment at the stack 52. The post-own-stack-searchdetection information 74 b includes the values of seriousness of eachpiece of equipment. The search results notifying unit 345 then transmitsthe generated post-own-stack-search detection information 74 b to theeffect range identifying device 400 in the lower-order stack 51.

The search results notifying unit 345 references the stack operationmodel 323 and generates display data 81 b indicating thefailure-detected equipment and failure-affected equipment at thehigher-order stack 53 and the stack 52 to which it belongs,respectively. The search results notifying unit 345 then transmits thedisplay data 81 b to the terminal device 30 that the administrator ofthe stack 52 uses. Thus, an image corresponding to the display data 81 bis displayed on the terminal device 30.

The image corresponding to the display data 81 b displays the connectionrelation among equipment within the stack 52, and the connectionrelation of equipment in the stack 52 and equipment in the higher-orderstack 53, for example. An image corresponding to the display data 81 bindicates the failure-detected equipment and failure-affected equipmentin a highlighted display. For example, settings are made in the displaydata 81 b so that the failure-detected equipment and failure-affectedequipment are displayed in different colors. Also, in the imagecorresponding to the display data 81 b, failure-affected equipment isdisplayed by a different color for each severity. Further, the values ofseriousness of corresponding equipment are displayed near objectsrepresenting the equipment in the image corresponding to the displaydata 81 b.

This so far is downflow processing according to the fourth embodiment.Seriousness is not updated in the upflow processing. Accordingly, theupflow processing according to the fourth embodiment is the same as inthe third embodiment.

FIG. 59 is a diagram illustrating an example of a stack operation modelin which is reflected the search results for the range of effects in theupflow processing according to the fourth embodiment. FIG. 59illustrates the stack operation model 323 in which the search resultsillustrated in FIG. 44 have been reflected. “1” has been added to thevalues of severity in the records for each of the equipment “aa”, “cc”,“dd”, “ee”, “ff”, and “gg” in the stack operation model 323.

Search results notification processing is performed based in such astack operation model 323.

FIG. 60 is a diagram illustrating an example of search resultsnotification processing in the upflow processing according to the fourthembodiment. The search results notifying unit 353 references the stackoperation model 323, and generates post-own-stack-search detectioninformation 76 indicating equipment in the higher-order stack 53connected to any of the failure-detected equipment and failure-affectedequipment in the stack 52. The search results notifying unit 353 thentransmits the generated post-own-stack-search detection information 76to the effect range identifying device 200 of the higher-order stack 53.

The search results notifying unit 353 also references the stackoperation model 323 and generates display data 82 b indicating thefailure-detected equipment and failure-affected equipment at thehigher-order stack 53 and the stack 52 to which it belongs,respectively. The display data 82 b has the display form forfailure-affected equipment set to a display form corresponding to theseverity. For example, the color of an object indicatingfailure-affected equipment is set to a different color for eachseverity. Further, objects indicating the values of seriousness ofcorresponding equipment are displayed near objects representing theequipment in the image corresponding to the display data 81 b.

The search results notifying unit 353 then transmits the display data 82b to the terminal device 30 that the administrator of the stack 52 uses.Thus, an image corresponding to the display data 82 b is displayed onthe terminal device 30.

Thus, the severity and seriousness of the failure regarding thefailure-detected equipment and failure-affected equipment is displayedat the terminal device 30. The administrator of the stack 52 mayreference the displayed image and appropriately judge the order ofpriority in which to handle the failure. For example, the administratorhandles equipment of which the severity or seriousness is apredetermined value or higher with priority.

Other Embodiments

In the second through fourth embodiments, the effects of failure atmultiple pieces of equipment detected at the same period are managed ina single stack operation model. This is because it may be assumed thatfailures occurring at the same period have some sort of relationship.However, with a large-scale system, there is a possibility that multiplefailures having different causes will occur at the same period.Accordingly, the effect range identifying devices 200, 300, and 400 maygenerate individual stack operation models each time the range ofeffects of a failure is searched for.

FIG. 61 is a diagram illustrating an example of generating a stackoperation model for each search for range of effects of failure. Forexample, the information collecting unit 343 generates equipmentinformation of the stack 52 and higher-order stack equipment informationof equipment connected to equipment of the stack 52, and creates a stackoperation model 324 made up of just connection information among thepieces of equipment. The information collecting unit 343 periodicallyupdates the stack operation model 324 to the newest information.

The effects searching unit 344 creates effects search stack operationmodels 324 a, 324 b, and so on, based on the stack operation model 324,each time a search is performed for the range of effects of failure. Theeffects search stack operation models 324 a, 324 b, and so on, include,in records for each piece of equipment, information of seriousness,whether or not a failure has occurred, severity, and whether or not tobe start point equipment. A failure-occurrence No., which an identifierof each failure occurring, is set in the effects search stack operationmodels 324 a, 324 b, and so on.

In a case of transmitting information to other effect range identifyingdevices, the effect range identifying devices 200, 300, and 400 attach,to the information being transmitted, the failure-occurrence No. of theeffects search stack operation model used to generate that information.

Accordingly, the effect range identifying devices 200, 300, and 400 maycooperate with each other, generate a failure-occurrence No. each timeoccurrence of a failure is detected at any equipment, and performanalysis of the range of effects of failure, and seriousness andseverity at each piece of equipment, for each failure-occurrence No.

There are cases where some stacks out of the multiple stacks in alayered structure have not introduced an effect range identifyingdevice. In this case, searching of effects of failure may be performedjust between stacks that have introduced effect range identifyingdevices.

FIG. 62 is a diagram illustrating an example of a cloud environmentincluding stacks that have not introduced effect range identifyingdevices. Multiple stacks 91 through 97 are in a layered structure inFIG. 62. Stack 92 and stack 93 are stacks in the same layer. Stack 95and stack 96 are also stacks in the same layer. In the example in FIG.62, effect range identifying devices 91 a, 92 a, 94 a, 95 a, and 97 a,realized by virtual machines, have been introduced to the stacks 91, 92,94, 95, and 97. No effect range identifying devices have been introducedto stacks 93 and 96. In this case, searching for range of effects offailure is performed just among the effect range identifying devices 91a, 92 a, 94 a, 95 a, and 97 a. As a result, the range of effects offailure propagating through the stacks 91, 92, 94, 95, and 97 may besearched for.

A case is also conceivable where there are multiple stacks operated bydifferent corporations in the same layer.

FIG. 63 is a diagram illustrating an example of a cloud environmentwhere there are multiple stacks operated by different corporations inthe same layer. In the example in FIG. 63, stack 95 and stack 96 outputthe stacks 91 through 97 are managed and operated by differentcorporations, despite being in the same layer. The effect rangeidentifying devices 91 a, 92 a, 94 a, 95 a, 96 a, and 97 a, realized byvirtual machines, have been introduced to the stacks 91, 92, and 94through 97. In such a case, in stacks that are vertically adjacent,failure effects searching across multiple stacks is performed by effectrange identifying devices among corporations that have introduced effectrange identifying devices.

The effect range identifying device may weight severity depending on thetype of equipment serving as a start point. For example, the effectrange identifying devices 200, 300, and 400 illustrated in the secondthrough fourth embodiments change the value to be added to the severityof equipment within the range of effects from the start point thereof,depending on whether the equipment serving as the start point isfailure-detected equipment or failure-affected equipment. If theequipment serving as the start point is failure-detected equipment, theseverity of equipment within the range of effects is incremented by “2”,while if the equipment serving as the start point is failure-affectedequipment, the severity of equipment within the range of effects isincremented by “1”, at the effect range identifying devices 200, 300,and 400. In a case where the equipment serving as the start point isfailure-detected equipment, equipment where an abnormality is actuallyoccurring is the start point, so a greater value is added to theseverity in this way, as compared to a case where the equipment servingas a start point is failure-affected equipment. Further, in a case wherethe equipment serving as a start point is failure-affected equipment,for example, the effect range identifying devices 200, 300, and 400 mayadd the severity of the equipment serving as the start point to theseverity of failure-affected equipment of which this equipment is thestart point.

Although embodiments have been exemplarily illustrated, theconfigurations of parts illustrated in the embodiments may be replacedby others having similar functions. Also, other optional configurationsand processes may be added. Further, any two or more configurations(features) of the above-described embodiments may be combined.

All examples and conditional language provided herein are intended forthe pedagogical purposes of aiding the reader in understanding theinvention and the concepts contributed by the inventor to further theart, and are not to be construed as limitations to such specificallyrecited examples and conditions, nor does the organization of suchexamples in the specification relate to a showing of the superiority andinferiority of the invention. Although one or more embodiments of thepresent invention have been described in detail, it should be understoodthat the various changes, substitutions, and alterations could be madehereto without departing from the spirit and scope of the invention.

What is claimed is:
 1. A computer-implemented method to detect range ofa range of effects of a failure within a cloud computing systemproviding cloud services having a layered structure of services, themethod comprising: obtaining, from a higher-order effect rangeidentifying device configured to search for a range of effects offailure within a higher-order service layer that provides a higher-orderservice using a service provided in an object service layer within thecloud computing system, an identifier of a detected higher-order serviceregarding which occurrence of an abnormality or a possibility of beingaffected by the abnormality has been detected; determining, based onsearch route information indicating a search route to search for aservice within a range of effects of failure from a start point service,a service within the object service layer that is reachable by tracingrelations among services from the detected higher-order service byfollowing a search route in a case where the detected higher-orderservice is the start point service, to be a first in-effect-rangeservice regarding which there is the possibility of being affected bythe abnormality; and transmitting the identifier of the firstin-effect-range service to a lower-order effect range identifying deviceconfigured to search for a range of effects of failure at a lower-orderservice layer, which is a source of providing a lower-order service thatis used to provide a service within the object service layer.
 2. Themethod of claim 1, further comprising: outputting display data, for ascreen display, indicating that the first in-effect-range service in theobject service layer is in the range of effects of failure.
 3. Themethod of claim 1, further comprising: obtaining, from the lower-ordereffect range identifying device, an identifier of a using service withinthe object service layer that uses the lower-order service determined tobe in the range of effects of failure, by the search for a failureeffect range based on the first in-effect-range service by thelower-order effect range identifying device; determining, based on thesearch route information, a service within the object service layer thatis reachable by tracing relations among services from the using serviceby following a search route in a case where the using service is thestart point service, to be a second in-effect-range service regardingwhich there is a possibility of being affected by an abnormality; andtransmitting an identifier of a using higher-order service using thesecond in-effect-range service out of the higher-order services withinthe higher-order service layer, to the higher-order effect rangeidentifying device.
 4. The method of claim 1, further comprising:determining, in a case where there are a plurality of the detectedhigher-order services, the first in-effect-range service with each ofthe plurality of detected higher-order services as the start pointservice; determining a value corresponding to a count of times where thefirst in-effect-range service has been judged to be reachable by tracingrelations among services from the detected higher-order services to be aseverity of failure of the first in-effect-range service; and outputtingseverity display data, for a screen display, of the severity of thefirst in-effect-range service in the object service layer.
 5. The methodof claim 1, further comprising: calculating a seriousness in a case ofthe first in-effect-range service being affected by failure, thecalculated seriousness based on a usage form of the firstin-effect-range service; and outputting seriousness display data, for ascreen display, of the seriousness of the first in-effect-range servicein the object service layer.
 6. The method of claim 5, wherein, in thecalculating the seriousness, a sum of a value calculated based on theusage form of the first in-effect-range service, and a value calculatedbased on a usage form of the higher-order service in the higher-orderservice layer using the first in-effect-range service, is calculated asthe seriousness of the first in-effect-range service.
 7. Anon-transitory, computer-readable recording medium having stored thereina program for causing a computer to execute a process, the processcomprising: obtaining, from a higher-order effect range identifyingdevice configured to search for a range of effects of failure within ahigher-order service layer that provides a higher-order service using aservice provided in an object service layer within a cloud service whereservices being provided have a layered structure, an identifier of adetected higher-order service regarding which occurrence of anabnormality or a possibility of being affected by an abnormality hasbeen detected; determining, based on search route information indicatinga search route to search for a service within a range of effects offailure from a start point service, a service within the object servicelayer that is reachable by tracing relations among services from thedetected higher-order service by following a search route in a casewhere the detected higher-order service is the start point service, tobe a first in-effect-range service regarding which there is apossibility of being affected by an abnormality; and transmitting theidentifier of the first in-effect-range service to a lower-order effectrange identifying device configured to search for a range of effects offailure at a lower-order service layer, which is a source of providing alower-order service that is used to provide a service within the objectservice layer.
 8. An apparatus comprising: a memory; and a processorcoupled to the memory and configured to: obtain, from a higher-ordereffect range identifying device configured to search for a range ofeffects of failure within a higher-order service layer that provides ahigher-order service using a service provided in an object service layerwithin a cloud service where services being provided have a layeredstructure, an identifier of a detected higher-order service regardingwhich occurrence of an abnormality or a possibility of being affected byan abnormality has been detected; determine, based on search routeinformation indicating a search route to search for a service within arange of effects of failure from a start point service, a service withinthe object service layer that is reachable by tracing relations amongservices from the detected higher-order service by following a searchroute in a case where the detected higher-order service is the startpoint service, to be a first in-effect-range service regarding whichthere is a possibility of being affected by an abnormality; and transmitthe identifier of the first in-effect-range service to a lower-ordereffect range identifying device configured to search for a range ofeffects of failure at a lower-order service layer, which is a source ofproviding a lower-order service that is used to provide a service withinthe object service layer.
 9. A computer-implemented method to detectrange of a range of effects of a failure within a cloud computing systemhaving a layered structure, the method comprising: detecting a failurewithin the cloud computer system, the cloud computer system including ahigher-order layer having a first range identifying device, object layerhaving a second range identifying device, and lower-order layer having athird range identifying device, the first range identifying device,second range identifying device and third range identifying deviceperform cooperative processing to detect the range of effects of thedetected failure; receiving, by the second range identifying device,identifiers of higher order equipment of which a failure is detected;searching, by the second range identifying device, for first in-effectrange equipment based on the received identifiers and route information,the route information identifying relationships between equipment withina same layer of the layered structure and relationships betweenequipment with different layers of the layered structure; transmitting,from the second range identifying device to the third range identifyingdevice, identifiers of the first in-effect range equipment; identifying,by the third range identifying device, lower-order equipment of thelower-order layer based on the identifiers of the first in-effect rangeequipment and the route information; transmitting, from the third rangeidentifying device to the second range identifying device, theidentifiers of the identified lower-order equipment; searching, by thesecond range identifying device, for second in-effect range equipmentbased on the route information and the identifiers of the lower-orderequipment; and outputting the range of effects of the detected failurethat identifies the detected higher order equipment, the searched firstin-effect range equipment, and the second in-effect range equipment.